ORCID Profile
0000-0002-9832-5959
Current Organisations
Rubicon Water
,
Federation University Australia - Berwick Campus
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Research Topics
In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Top 5 Research Topics
ANZSRC Field of Research (FoR)
Systems Theory And Control | Electrical and Electronic Engineering | Applied Mathematics | Artificial Intelligence and Image Processing | Control Systems, Robotics and Automation | Information Storage, Retrieval And Management | Image Processing | Dynamical Systems in Applications | Interorganisational Information Systems | Electrical Engineering | Optimisation | Signal Processing | Automation and Control Engineering | Power and Energy Systems Engineering (excl. Renewable Power) | Systems Theory | Systems Biology | Stochastic Analysis And Modelling | Optimisation | Information Systems Management | Research, Science And Technology Policy | Robotics And Mechatronics | Motor Control | Interdisciplinary Engineering | Quantum Optics And Lasers | Dynamical Systems | Numerical and Computational Mathematics | Pure Mathematics | Simulation And Modelling | Biomechanics | Engineering And Technology Not Elsewhere Classified | Medical Devices | Biomedical Engineering | Biomechanical Engineering | Numerical Analysis | Computer Communications Networks | Pattern Recognition and Data Mining | Calculus of Variations, Systems Theory and Control Theory | Analysis Of Algorithms And Complexity | Operations Research | Stochastic Analysis and Modelling | Interdisciplinary Engineering Not Elsewhere Classified | Neurology And Neuromuscular Diseases | Central Nervous System |
ANZSRC Socio-Economic Objective (SEO)
Information processing services | Mathematical sciences | Expanding Knowledge in Engineering | Application tools and system utilities | Combined operations | Land and water management | Energy Services and Utilities | Expanding Knowledge in the Mathematical Sciences | Air Force | Application packages | Native forests | Industry | Physical sciences | Automotive equipment | Other | Industry policy | Information services not elsewhere classified | Industry costs and structure | Industrial Machinery and Equipment | Skeletal system and disorders (incl. arthritis) | Computer hardware and electronic equipment not elsewhere classified | Technological and organisational innovation | Health and Support Services not elsewhere classified | Nervous system and disorders | Diagnostic methods | Expanding Knowledge in the Medical and Health Sciences | Expanding Knowledge in Technology | Urban and Industrial Water Management | Industrial Energy Conservation and Efficiency | Energy Conservation and Efficiency in Transport | Computer software and services not elsewhere classified | Transport equipment not elsewhere classified | Expanding Knowledge in the Information and Computing Sciences | Expanding Knowledge in the Biological Sciences | Communication equipment not elsewhere classified | Other
Related Links
Publications
Non-linear dynamics in adaptive control: Chaotic and periodic stabilization
Publisher: Elsevier BV
Date: 11-1986
Solutions to disturbance decoupling problem with constant measurement feedback for linear systems
Publisher: Elsevier BV
Date: 11-2000
A small-gain control method for nonlinear cascaded systems with dynamic uncertainties
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-1997
DOI: 10.1109/9.557574
A Lyapunov formulation of the nonlinear small-gain theorem for interconnected ISS systems
Publisher: Elsevier BV
Date: 08-1996
A dual purpose principal and minor component flow
Publisher: Elsevier BV
Date: 08-2005
Robustness analysis of leader-follower consensus
Publisher: Springer Science and Business Media LLC
Date: 02-05-2009
Self-tuning control for polynomial systems using a receding horizon observer and control strategy
Publisher: Wiley
Date: 30-04-2004
DOI: 10.1002/ACS.800
Maximum parsimony, substitution model, and probability phylogenetic trees
Publisher: Mary Ann Liebert Inc
Date: 2011
Abstract: The problem of inferring phylogenies (phylogenetic trees) is one of the main problems in computational biology. There are three main methods for inferring phylogenies-Maximum Parsimony (MP), Distance Matrix (DM) and Maximum Likelihood (ML), of which the MP method is the most well-studied and popular method. In the MP method the optimization criterion is the number of substitutions of the nucleotides computed by the differences in the investigated nucleotide sequences. However, the MP method is often criticized as it only counts the substitutions observable at the current time and all the unobservable substitutions that really occur in the evolutionary history are omitted. In order to take into account the unobservable substitutions, some substitution models have been established and they are now widely used in the DM and ML methods but these substitution models cannot be used within the classical MP method. Recently the authors proposed a probability representation model for phylogenetic trees and the reconstructed trees in this model are called probability phylogenetic trees. One of the advantages of the probability representation model is that it can include a substitution model to infer phylogenetic trees based on the MP principle. In this paper we explain how to use a substitution model in the reconstruction of probability phylogenetic trees and show the advantage of this approach with ex les.
Two scale high gain adaptive control
Publisher: Wiley
Date: 30-04-2004
DOI: 10.1002/ACS.802
RECOVERING STATE TRAJECTORIES FROM OUTPUT MEASUREMENTS AND DYNAMIC MODELS: A COMPUTATIONAL COMPLEXITY POINT OF VIEW
Publisher: World Scientific Pub Co Pte Lt
Date: 05-2002
DOI: 10.1142/S0218127402004929
Abstract: Prediction, smoothing, filtering and synchronization or observer design given finitely many measurements and a given (possibly nonlinear) dynamical map are discussed from a computational complexity point of view. All these problems are particular instances of finding a zero of an appropriately defined function. The recognition of this fact enables one to approach these questions from a computational complexity point of view. For polynomial maps the computational complexity of a global Newton algorithm adapted to identify the finite trajectory of the dynamical system's state over the desired window scales in a polynomial manner with the condition number (an invariant for the problem at hand) and the degree of the polynomials required to describe the models. The computational complexity analysis allows one to identify the most efficient manner to approach synchronization (prediction, smoothing, filtering) problems. Moreover differences between adaptive and nonadaptive formulations are revealed based on the condition number of the associated zero finding problem. The advocated formulation, with the associated global Newton algorithm has good robustness properties with respect to measurement errors and model errors for both adaptive and nonadaptive problems. These aspects are illustrated through a simulation study based around the Hénon map.
Electric vehicle charging and grid constraints: Comparing distributed and centralized approaches
Publisher: IEEE
Date: 2013
Bayesian model evidence for order selection and correlation testing
Publisher: IEEE
Date: 08-2011
Model-based predictive sampled-data control and its robustness
Publisher: IEEE
Date: 05-2015
Modeling of Endpoint Feedback Learning Implemented Through Point-to-Point Learning Control
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2017
A GFSK demodulator for ultra-low power MICS band receiver
Publisher: IEEE
Date: 12-2010
On experimentally validated iterative learning control in human motor systems
Publisher: IEEE
Date: 06-2014
Comment on a comparative testing study of commercial 18650-format lithium-ion battery cells [J. Electrochem. Soc., 162, A1592 (2015)]
Publisher: The Electrochemical Society
Date: 2015
DOI: 10.1149/2.0241512JES
Weak Monotonicity With Trend Analysis for Unsupervised Feature Evaluation
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2023
An analysis of the fast subspace tracking algorithm NOja
Publisher: IEEE
Date: 05-2002
Non-linear stable inversion-based output tracking control for a spherical inverted pendulum
Publisher: Informa UK Limited
Date: 2008
Reconstruction of probability phylogenetic trees with substitution models
Publisher: IEEE
Date: 06-2009
Comments on “Adaptive Control of Linearizable Systems”
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-1992
DOI: 10.1109/9.135521
Dual stage actuator control in hard disk drive - a review
Publisher: IEEE
Date: 2003
Modeling reversible self-discharge in series-connected Li-ion battery cells
Publisher: IEEE
Date: 04-2013
Feedback-Based Iterative Learning Design and Synthesis With Output Constraints for Robotic Manipulators
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2018
Experimental and Theoretical Comparison of Some Algorithms for Beamforming in Single Receiver Adaptive Arrays
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 1991
DOI: 10.1109/8.64430
A ultra low power, wide input range MICS band channel selection filter on 65 nm CMOS
Publisher: IEEE
Date: 11-2010
Optimal charging of electric vehicles taking distribution network constraints into account
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2015
On non-local stability properties of extremum seeking control
Publisher: Elsevier BV
Date: 06-2006
Robust nonlinear integral control
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2001
DOI: 10.1109/9.940947
Patient Un-Specific Detection of Epileptic Seizures Through Changes in Variance
Publisher: IEEE
Date: 08-2006
Model-guided data-driven decentralized control for magnetic levitation systems
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2018
Finite sample properties of linear model identification
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-1999
DOI: 10.1109/9.774109
Analysis and Control of the Signal Dependent Performance of Adaptive Echo Cancellers in 4-Wire Loop Telephony
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-1995
DOI: 10.1109/82.392313
Obfuscated Memory Malware Detection in Resource-Constrained IoT Devices for Smart City Applications
Publisher: MDPI AG
Date: 05-06-2023
DOI: 10.3390/S23115348
Abstract: Obfuscated Memory Malware (OMM) presents significant threats to interconnected systems, including smart city applications, for its ability to evade detection through concealment tactics. Existing OMM detection methods primarily focus on binary detection. Their multiclass versions consider a few families only and, thereby, fail to detect much existing and emerging malware. Moreover, their large memory size makes them unsuitable to be executed in resource-constrained embedded/IoT devices. To address this problem, in this paper, we propose a multiclass but lightweight malware detection method capable of identifying recent malware and is suitable to execute in embedded devices. For this, the method considers a hybrid model by combining the feature-learning capabilities of convolutional neural networks with the temporal modeling advantage of bidirectional long short-term memory. The proposed architecture exhibits compact size and fast processing speed, making it suitable for deployment in IoT devices that constitute the major components of smart city systems. Extensive experiments with the recent CIC-Malmem-2022 OMM dataset demonstrate that our method outperforms other machine learning-based models proposed in the literature in both detecting OMM and identifying specific attack types. Our proposed method thus offers a robust yet compact model executable in IoT devices for defending against obfuscated malware.
Reduced-Complexity Estimation for Large-Scale Hidden Markov Models
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2004
Feedback and Control for Everyone (Albertos, P. and Mareels, I.; 2010) [Bookshelf]
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2011
Soft sensor for flow measurement: overshot regulator
Publisher: IEEE
Date: 1999
Fourier Tract Sampling (FouTS): A framework for improved inference of white matter tracts from diffusion MRI by explicitly modelling tract volume
Publisher: Elsevier BV
Date: 10-2015
DOI: 10.1016/J.NEUROIMAGE.2015.05.090
Abstract: Diffusion MRI tractography algorithm development is increasingly moving towards global techniques to incorporate "downstream" information and conditional probabilities between neighbouring tracts. Such approaches also enable white matter to be represented more tangibly than the abstract lines generated by the most common approaches to fibre tracking. However, previously proposed algorithms still use fibre-like models of white matter corresponding to thin strands of white matter tracts rather than the tracts themselves, and therefore require many components for accurate representations, which leads to poorly constrained inverse problems. We propose a novel tract-based model of white matter, the 'Fourier tract', which is able to represent rich tract shapes with a relatively low number of parameters, and explicitly decouples the spatial extent of the modelled tract from its 'Apparent Connection Strength (ACS)'. The Fourier tract model is placed within a novel Bayesian framework, which relates the tract parameters directly to the observed signal, enabling a wide range of acquisition schemes to be used. The posterior distribution of the Bayesian framework is characterised via Markov-chain Monte-Carlo s ling to infer probable values of the ACS and spatial extent of the imaged white matter tracts, providing measures that can be directly applied to many research and clinical studies. The robustness of the proposed tractography algorithm is demonstrated on simulated basic tract configurations, such as curving, twisting, crossing and kissing tracts, and sections of more complex numerical phantoms. As an illustration of the approach in vivo, fibre tracking is performed on a central section of the brain in three subjects from 60 direction HARDI datasets.
Control of Large-Scale Irrigation Networks
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2007
Modeling and validation of an unbalanced LV network using Smart Meter and SCADA inputs
Publisher: IEEE
Date: 04-2013
Stability Theory for Differential/Algebraic Systems with Application to Power Systems
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 1990
DOI: 10.1109/31.62415
On on-line sampled-data optimal learning for dynamic systems with uncertainties
Publisher: IEEE
Date: 06-2013
A fully flexible stimulator using 65 nm CMOS process for 1024-electrode epi-retinal prosthesis
Publisher: IEEE
Date: 09-2009
Complex Stability Radius for Automatic Design of Gain-Scheduled Control Part II: Example on Autopilot Design
Publisher: Springer Berlin Heidelberg
Date: 2007
Extremum seeking for constrained inputs
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2013
Complex Stability Radius for Automatic Design of Gain-Scheduled Control Part I: Theoretical Developm
Publisher: Springer Berlin Heidelberg
Date: 2007
Power sharing correction in angle droop controlled inverter interfaced microgrids
Publisher: IEEE
Date: 07-2015
Set-Membership Identification for Adaptive Control: Input Design
Publisher: IEEE
Date: 2003
Optimal switching control of AC-DC bridge converters for DC power system applications
Publisher: IEEE
Date: 1998
Controlling DC microgrids in communities, buildings and data centers
Publisher: Institution of Engineering and Technology (IET)
Date: 15-05-2020
Sufficient conditions for the existence of an unbounded solution
Publisher: Elsevier BV
Date: 10-2001
Evaluating Rehabilitation Progress Using Motion Features Identified by Machine Learning
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2021
Adaptive repetitive learning control of robotic manipulators without the requirement for initial repositioning
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2006
On sign-definite pairs of functions
Publisher: IEEE
Date: 06-2014
Dynamics of an adaptive hybrid
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 1991
DOI: 10.1109/31.101298
Excitation Conditions for Signed Regressor Least Mean Squares Adaptation
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-1988
DOI: 10.1109/31.1799
The validity of predicting maximal oxygen uptake from a perceptually-regulated graded exercise test
Publisher: Springer Science and Business Media LLC
Date: 07-04-2005
DOI: 10.1007/S00421-005-1327-2
Abstract: The purpose of this study was to assess the validity of predicting maximal oxygen uptake(VO(2max)) from sub-maximal VO(2) values elicited during a perceptually-regulated exercise test. We hypothesised that the strong relationship between the ratings of perceived exertion (RPE) and VO(2) would enable VO(2max) to be predicted and that this would improve with practice. Ten male volunteers performed a graded exercise test (GXT) to establish VO(2max) followed by three sub-maximal RPE production protocols on a cycle ergometer, each separated by a period of 48 h. The perceptually-regulated trials were conducted at intensities of 9, 11, 13, 15 and 17 on the RPE scale, in that order. VO(2) and HR were measured continuously and recorded at the end of each 4 min stage. In idual's RPE values yielded correlations in the range 0.92-0.99 across the three production trials. There were no significant differences between measured VO(2max) (48.8 ml.kg(-1).min(-1)) and predicted VO(2) max values (47.3, 48.6 and 49.9 ml.kg(-1).min(-1), for trials 1, 2 and 3, respectively) when VO(2) max was predicted from RPE values of 9-17. The same was observed when VO(2max) was predicted using RPE 9-15. Limits of agreement (LoA) analysis on actual and predicted VO(2max) values (from RPE 9-17) were (bias+/-1.96xSDdiff) 1.5+/-7.3, 0.2+/-4.9 and -1.2+/-5.8 ml.kg(-1).min(-1), for trials 1, 2 and 3, respectively. Corresponding LoA values for actual and predicted VO(2max) (from RPE 9-15) were 5.4+/-11.3, 4.4+/-8.7 and 2.3+/-8.4 ml.kg(-1).min(-1), respectively. The data suggest that a sub-maximal, perceptually-guided, graded exercise protocol can provide acceptable estimates of maximal aerobic power, which are further improved with practice in fit young males.
Input and Output Constraints in Iterative Learning Control Design for Robotic Manipulators
Publisher: World Scientific Pub Co Pte Lt
Date: 07-2018
DOI: 10.1142/S2301385018400095
Abstract: Motivated by the safety requirement of rehabilitation robotic systems for after stroke patients, this paper handles position or output constraints in robotic manipulators when the patients repeat the same task with the robot. In order to handle output constraints, if all state information is available, a state feedback controller can ensure that the output constraints are satisfied while iterative learning control (ILC) is used to learn the desired control input through iterations. By incorporating the feedback control using barrier Lyapunov function with feed-forward control (ILC) carefully, the convergence of the tracking error, the boundedness of the internal state, the boundedness of input signals can be guaranteed along with the satisfaction of the output constraints over iterations. The effectiveness of the proposed controller is demonstrated using simulations from the model of EMU, a rehabilitation robotic system.
Effect of sensory experience on motor learning strategy
Publisher: American Physiological Society
Date: 15-02-2015
Abstract: It is well known that the central nervous system automatically reduces a mismatch in the visuomotor coordination. Can the underlying learning strategy be modified by environmental factors or a subject's learning experiences? To elucidate this matter, two groups of subjects learned to execute reaching arm movements in environments with task-irrelevant visual cues. However, one group had previous experience of learning these movements using task-relevant visual cues. The results demonstrate that the two groups used different learning strategies for the same visual environment and that the learning strategy was influenced by prior learning experience.
Detection of arcing in DC motors
Publisher: IEEE
Date: 1999
Dual-loop iterative optimal control for the finite horizon LQR problem with unknown dynamics
Publisher: Elsevier BV
Date: 2018
Putting energy back in control
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2001
DOI: 10.1109/37.915398
On making energy demand and network constraints compatible in the last mile of the power grid
Publisher: Elsevier BV
Date: 2014
On the finite time performance of model predictive control
Publisher: Elsevier BV
Date: 08-2014
Power Sharing in Angle Droop Controlled Microgrids
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2017
Decision region approximation by polynomials or neural networks
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-1997
DOI: 10.1109/18.568700
A simple selftuning controller for stably invertible systems
Publisher: Elsevier BV
Date: 02-1984
A Probabilistic Reverse Power Flows Scenario Analysis Framework
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Patient-specific bivariate-synchrony-based seizure prediction for short prediction horizons
Publisher: Elsevier BV
Date: 10-2010
DOI: 10.1016/J.EPLEPSYRES.2010.07.014
Abstract: This paper evaluates the patient-specific seizure prediction performance of pre-ictal changes in bivariate-synchrony between pairs of intracranial electroencephalographic (iEEG) signals within 15min of a seizure in patients with pharmacoresistant focal epilepsy. Prediction horizons under 15min reduce the durations of warning times and should provide adequate time for a seizure control device to intervene. Long-term continuous iEEG was obtained from 6 patients. The seizure prediction performance was evaluated for all possible channel pairs and for different prediction methods to find the best performing channel pairs and methods for both pre-ictal decreases and increases in synchrony. The different prediction methods involved changes in window duration, signal filtering, thresholding approach, and prediction horizon durations. Performance for each patient, for all seizures, was first compared with an analytical-Poisson-based random predictor. The performance of the top 5% of channel pairs for each patient closely matched the top 5% of analytical-Poisson-based random predictor performance indicating that patient-specific, bivariate-synchrony-based seizure prediction could be random in general (under the assumption that channel-pair prediction times are statistically independent). Analysis of the spatial patterns of performance showed no clear relationship to the seizure onset zone. For each patient the best channel pair showed better performance than Poisson-based random prediction for a selected subset of prediction thresholds. Given the caveats of comparing with this form of random prediction, alarm time surrogates were employed to assess statistical significance of a four-fold out-of-s le cross-validation analysis applied to the best channel-pairs. The cross-validation analysis obtained reasonable testing performance for most patients when performance was compared to random prediction based on alarm time surrogates. The most significant case was a patient whose testing set sensitivity and false positive rate were 0.67±0.09 and 3.04±0.29h(-1), respectively, for decreases in synchrony, an intervention time of 15min and a seizure onset period of 5min. For each testing set for this patient, performance was better than that obtained by random prediction at the significance level of 0.05 (average sensitivity of 0.47±0.05). Moreover, there were 9 seizures in each testing set which gives greater power to this cross-validation result, although the cross-validation was performed on the best channel pair selected by within-s le optimization for all seizures of the patient. Further validation with larger datasets from in idual patients is needed. Improvements in prediction performance should be achievable through investigations of multivariate synchrony combined with non-linear classification methods.
A Market Mechanism for Electric Vehicle Charging under Network Constraints
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2016
Systems engineering for irrigation systems: Successes and challenges
Publisher: Elsevier BV
Date: 2005
Analyzing the Stability of Switched Systems Using Common Zeroing-Output Systems
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2017
Robustness analysis of leader-follower consensus
Publisher: IEEE
Date: 07-2008
A subthreshold down converter optimized for super-low-power applications in MICS band
Publisher: IEEE
Date: 11-2011
On Feedback-Based Iterative Learning Control for Nonlinear Systems Without Global Lipschitz Continuity
Publisher: IEEE
Date: 06-2018
Nonlinear averaging theorems, and the determination of parameter convergence rates in adaptive control
Publisher: Elsevier BV
Date: 06-1986
A comparison study of commercial 18650-format lithium-ion battery cells
Publisher: The Electrochemical Society
Date: 2015
DOI: 10.1149/2.0721508JES
Siting and sizing distributed storage for microgrid applications
Publisher: IEEE
Date: 10-2017
The power of spectral density analysis for mapping endogenous BOLD signal fluctuations
Publisher: Wiley
Date: 02-05-2008
DOI: 10.1002/HBM.20601
On the effect of component mismatches in inverter interfaced microgrids
Publisher: IEEE
Date: 09-2014
Stability and motor adaptation in human arm movements
Publisher: Springer Science and Business Media LLC
Date: 11-11-2005
DOI: 10.1007/S00422-005-0025-9
Abstract: In control, stability captures the reproducibility of motions and the robustness to environmental and internal perturbations. This paper examines how stability can be evaluated in human movements, and possible mechanisms by which humans ensure stability. First, a measure of stability is introduced, which is simple to apply to human movements and corresponds to Lyapunov exponents. Its application to real data shows that it is able to distinguish effectively between stable and unstable dynamics. A computational model is then used to investigate stability in human arm movements, which takes into account motor output variability and computes the force to perform a task according to an inverse dynamics model. Simulation results suggest that even a large time delay does not affect movement stability as long as the reflex feedback is small relative to muscle elasticity. Simulations are also used to demonstrate that existing learning schemes, using a monotonic antisymmetric update law, cannot compensate for unstable dynamics. An impedance compensation algorithm is introduced to learn unstable dynamics, which produces similar adaptation responses to those found in experiments.
Lavoisier’s “Reflections on phlogiston” II: on the nature of heat
Publisher: Springer Science and Business Media LLC
Date: 16-07-2015
Sufficiency of excitation
Publisher: Elsevier BV
Date: 12-1984
Invariance Principles and Observability in Switched Systems With an Application in Consensus
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2021
A flexible electrode driver using 65 nm CMOS process for 1024-electrode Epi-retinal prosthesis
Publisher: IEEE
Date: 2010
On the choice of dither in extremum seeking systems: A case study
Publisher: Elsevier BV
Date: 05-2008
Passivity-based control for flight control systems
Publisher: IEEE
Date: 1999
A generalized dynamical model for three-phase switch-mode converter circuits
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2003
Predicting stand basal area in thined stands using a dynamical model
Publisher: Elsevier BV
Date: 04-1999
Limitations of Robust Adaptive Pole Placement Control
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 1994
DOI: 10.1109/9.310046
Modelling and control for an EMS system with two inputs
Publisher: Inderscience Publishers
Date: 2012
Extremum Seeking Control With Sporadic Packet Transmission for Networked Control Systems
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2020
Misperception
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 12-2015
Output deadbeat control of nonlinear discrete-time systems with one-dimensional zero dynamics: Global stability conditions
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-1999
DOI: 10.1109/9.769387
Feature Learning in Assistive Rehabilitation Robotic Systems
Publisher: IEEE
Date: 07-2018
Change detection in Markov-modulated time series
Publisher: IEEE
Date: 1999
Enhanced detection-guided NLMS estimation of sparse FIR-modeled signal channels
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2006
A super low power MICS band receiver in 65 nrn CMOS for high resolution epi-retinal prosthesis
Publisher: IEEE
Date: 10-2009
Upper Limb Deweighting Using Underactuated End-Effector-Based Backdrivable Manipulanda
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2018
A new condition for output-persistent-excitation of switched nonlinear time-varying systems
Publisher: IEEE
Date: 12-2018
Modelling extracellular electrical stimulation: Part 3. Derivation and interpretation of neural tissue equations
Publisher: IOP Publishing
Date: 24-11-2014
DOI: 10.1088/1741-2560/11/6/065004
Abstract: A common approach in modelling extracellular electrical stimulation is to represent neural tissue by a volume conductor when calculating the activating function as the driving term in a cable equation for the membrane potential. This approach ignores the cellular composition of tissue, including the neurites and their combined effect on the extracellular potential. This has a number of undesirable consequences. First, the two natural and equally valid choices of boundary conditions for the cable equation (i.e. using either voltage or current) lead to two mutually inconsistent predictions of the membrane potential. Second, the spatio-temporal distribution of the extracellular potential can be strongly affected by the combined cellular composition of the tissue. In this paper, we develop a mean field volume conductor theory to overcome these shortcomings of available models. This method connects the microscopic properties of the constituent fibres to the macroscopic electrical properties of the tissue by introducing an admittivity kernel for the neural tissue that is non-local, non-instantaneous and anisotropic. This generalizes the usual tissue conductivity. A class of bidomain models that is mathematically equivalent to this class of self-consistent volume conductor models is also presented. The bidomain models are computationally convenient for simulating the activation map of neural tissue using numerical methods such as finite element analysis. The theory is first developed for tissue composed of identical, parallel fibres and then extended to general neural tissues composed of mixtures of neurites with different and arbitrary orientations, arrangements and properties. Equations describing the extracellular and membrane potential for the longitudinal and transverse modes of stimulation are derived. The theory complements our earlier work, which developed extensions to cable theory for the micro-scale equations of neural stimulation that apply to in idual fibres. The modelling framework provides a number of advantages over other approaches currently adopted in the literature and, therefore, can be used to accurately estimate the membrane potential generated by extracellular electrical stimulation.
Assessment of voltage stability risks under stochastic net loads using scalable SVM classification
Publisher: IEEE
Date: 11-2018
Modelling extracellular electrical stimulation: Part 4. Effect of the cellular composition of neural tissue on its spatio-temporal filtering properties
Publisher: IOP Publishing
Date: 24-11-2014
DOI: 10.1088/1741-2560/11/6/065005
Abstract: The objective of this paper is to present a concrete application of the cellular composite model for calculating the membrane potential, described in an accompanying paper. A composite model that is used to determine the membrane potential for both longitudinal and transverse modes of stimulation is demonstrated. Two extreme limits of the model, near-field and far-field for an electrode close to or distant from a neuron, respectively, are derived in this paper. Results for typical neural tissue are compared using the composite, near-field and far-field models as well as the standard isotropic volume conductor model. The self-consistency of the composite model, its spatial profile response and the extracellular potential time behaviour are presented. The magnitudes of the longitudinal and transverse components for different values of electrode-neurite separations are compared. The unique features of the composite model and its simplified versions can be used to accurately estimate the spatio-temporal response of neural tissue to extracellular electrical stimulation.
Modeling individual human motor behavior through model reference iterative learning control
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2012
The principle of critical simplification in chemical kinetics
Publisher: Elsevier BV
Date: 11-2003
A software tool to generate simulated white matter structures for the assessment of fibre-tracking algorithms
Publisher: Elsevier BV
Date: 10-2009
DOI: 10.1016/J.NEUROIMAGE.2009.03.077
Abstract: The assessment of Diffusion-Weighted MRI (DW-MRI) fibre-tracking algorithms has been limited by the lack of an appropriate 'gold standard'. Practical limitations of alternative methods and physical models have meant that numerical simulations have become the method of choice in practice. However, previous numerical phantoms have consisted of separate fibres embedded in homogeneous backgrounds, which do not capture the true nature of white matter. In this paper we describe a method that is able to randomly generate numerical structures consisting of densely packed bundles of fibres, which are much more representative of human white matter, and simulate the DW-MR images that would arise from them under many imaging conditions. User-defined parameters may be adjusted to produce structures with a range of complexities that spans the levels we would expect to find in vivo. These structures are shown to contain many different features that occur in human white matter and which could confound fibre-tracking algorithms, such as tract kissing and crossing. Furthermore, combinations of such features can be s led by the random generation of many different structures with consistent levels of complexity. The proposed software provides means for quantitative assessment via direct comparison between tracking results and the exact location of the generated fibres. This should greatly improve our understanding of algorithm performance and therefore prove an important tool for fibre tracking development.
Static-state feedback laws for output regulation of non-linear systems
Publisher: Elsevier BV
Date: 07-1996
Lethal Stereotypes: Hair and Eye Color as Survival Characteristics During the Holocaust1
Publisher: Wiley
Date: 11-2002
On global extremum seeking in the presence of local extrema
Publisher: Elsevier BV
Date: 2009
Stability theory of differential/algebraic models of power systems
Publisher: Springer Science and Business Media LLC
Date: 09-1993
DOI: 10.1007/BF03024222
Quantifying task similarity for skill generalisation in the context of human motor control
Publisher: IEEE
Date: 11-2016
On the modelling complexity and utility of an EMS system
Publisher: IEEE
Date: 12-2010
A Complete Strategy for Patient Un-specific Detection of Epileptic Seizures Using Crude Estimations of Entropy
Publisher: IEEE
Date: 08-2007
3D model-based approach to identification of laminar structures of the cerebral cortex: Application to Brodmann areas 17 and 18
Publisher: Elsevier BV
Date: 11-2013
Indirect field-oriented control of induction motors is robustly globally stable
Publisher: Elsevier BV
Date: 10-1996
A tracking approach to parcellation of the cerebral cortex
Publisher: Springer Berlin Heidelberg
Date: 2005
DOI: 10.1007/11566465_37
Abstract: The cerebral cortex is composed of regions with distinct laminar structure. Functional neuroimaging results are often reported with respect to these regions, usually by means of a brain "atlas". Motivated by the need for more precise atlases, and the lack of model-based approaches in prior work in the field, this paper introduces a novel approach to parcellating the cortex into regions of distinct laminar structure, based on the theory of target tracking. The cortical layers are modelled by hidden Markov models and are tracked to determine the Bayesian evidence of layer hypotheses. This model-based parcellation method, evaluated here on a set of histological images of the cortex, is extensible to 3-D images.
On non-local vibrational stabilization of nonlinear systems
Publisher: IEEE
Date: 12-2018
Dynamic models and discrete event simulation
Publisher: Elsevier BV
Date: 05-1991
The Effects of Measurement Distance on the Broadside Symmetric Leaky Wave Antenna
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2008
Point-wise extremum seeking control scheme under repeatable control environment
Publisher: IEEE
Date: 2008
Seizure Detection Using Seizure Probability Estimation: Comparison of Features Used to Detect Seizures
Publisher: Springer Science and Business Media LLC
Date: 10-07-2009
DOI: 10.1007/S10439-009-9755-5
Abstract: This paper analyses seizure detection features and their combinations using a probability-based scalp EEG seizure detection framework developed by Marc Saab and Jean Gotman. Our method was evaluated on 525 h of data, including 88 seizures in 21 patients. The in idual performances of the three features used by Saab and Gotman were compared to six alternative features, and combinations of these nine features were analyzed in order to find a superior detector. On a testing set with the combination of their three features, Saab and Gotman reported a sensitivity of 0.78, a false positive rate of 0.86/h, and a median detection delay of 9.8 s. Based on 10-fold cross-validation the testing performance of our implementation of their method achieved a sensitivity of 0.79, a false positive rate of 0.62/h, and a median detection delay of 21.3 s. A detector based on an alternative combination of features achieved sensitivity of 0.81, a false positive rate of 0.60/h, and a median detection delay of 16.9 s. By including filtering techniques, it was possible to achieve performance levels similar to Saab and Gotman using our implementation of their method, although this involved increases in detection delays. Of the seizure detection measures investigated, relative average litude, relative power, relative derivative, and coefficent of variation of litude provided the best performing combinations. These better-performing features can be employed together to make robust and reliable seizure detectors.
Personalised Public Transportation: A new mobility model for urban and suburban transportation
Publisher: IEEE
Date: 10-2014
Correlation analysis of seizure detection features
Publisher: IEEE
Date: 12-2008
An observer looks at synchronization
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 1997
DOI: 10.1109/81.633877
Adaptively controlling non‐linear systems, using trajectory approximations
Publisher: Wiley
Date: 07-1992
Persistency of excitation criteria for linear, multivariable, time-varying systems
Publisher: Springer Science and Business Media LLC
Date: 10-1988
DOI: 10.1007/BF02551284
Nonlinear Energy-Based Control Method for Aircraft Automatic Landing Systems
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2010
EMU: A transparent 3D robotic manipulandum for upper-limb rehabilitation
Publisher: IEEE
Date: 07-2017
A unifying framework for global regulation via nonlinear output feedback: From ISS to iISS
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2004
Echo Canceler Performance Analysis in Four-Wire Loop Systems with Correlated AR Subscriber Signals
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 1995
DOI: 10.1109/18.370089
Robust nonlinear integral control by partial-state and output feedback
Publisher: IEEE
Date: 2000
On a new uniform dynamic coding algorithm for model-based networked control systems
Publisher: IEEE
Date: 11-2015
A rigorous solution of the infinite time interval LQ problem with constant state tracking
Publisher: Elsevier BV
Date: 07-2004
Decentralized control design of interconnected chains of integrators: A case study
Publisher: Elsevier BV
Date: 08-2008
Way Point Tracking of a Spherical Inverted Pendulum
Publisher: IEEE
Date: 05-2007
Local measurements and virtual pricing signals for residential demand side management
Publisher: Elsevier BV
Date: 12-2015
Fault detection in geared transmission systems using an acoustic array
Publisher: IEEE
Date: 1999
Performance comparison of adaptive and robust predictors for long range dependent signals
Publisher: IEEE
Date: 2000
Modelling of human motor control in an unstable task through operational space formulation
Publisher: IEEE
Date: 12-2010
Non-linear dynamics in adaptive control
Publisher: Elsevier BV
Date: 07-1988
Dead-beat control of simple Hammerstein models
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 1998
DOI: 10.1109/9.704998
Dead beat controllability of polynomial systems: Symbolic computation approaches
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 1998
DOI: 10.1109/9.661065
Design of feedback gain in feedback-based iterative learning control
Publisher: IEEE
Date: 12-2018
Improving the time efficiency of the Fourier synthesis method for slice selection in magnetic resonance imaging
Publisher: Elsevier BV
Date: 2016
DOI: 10.1016/J.EJMP.2015.10.088
Abstract: The design of slice selective pulses for magnetic resonance imaging can be cast as an optimal control problem. The Fourier synthesis method is an existing approach to solve these optimal control problems. In this method the gradient field as well as the excitation field are switched rapidly and their litudes are calculated based on a Fourier series expansion. Here, we provide a novel insight into the Fourier synthesis method via representing the Bloch equation in spherical coordinates. Based on the spherical Bloch equation, we propose an alternative sequence of pulses that can be used for slice selection which is more time efficient compared to the original method. Simulation results demonstrate that while the performance of both methods is approximately the same, the required time for the proposed sequence of pulses is half of the original sequence of pulses. Furthermore, the slice selectivity of both sequences of pulses changes with radio frequency field inhomogeneities in a similar way. We also introduce a measure, referred to as gradient complexity, to compare the performance of both sequences of pulses. This measure indicates that for a desired level of uniformity in the excited slice, the gradient complexity for the proposed sequence of pulses is less than the original sequence.
Traffic Reduction in Packet Switched Networked Control Systems Using Deadband Error Modulation
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2017
Controllability of structured polynomial systems
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-1999
DOI: 10.1109/9.754813
A prototype 64-electrode stimulator in 65 nm CMOS process towards a high density epi-retinal prosthesis
Publisher: IEEE
Date: 08-2011
Model predictive motion control of autonomous forklift vehicles with dynamics balance constraint
Publisher: IEEE
Date: 11-2017
Number/theoretic solutions to intercept time problems
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-1996
DOI: 10.1109/18.490557
Stereotype formation: Biased by association.
Publisher: American Psychological Association (APA)
Date: 2010
DOI: 10.1037/A0018210
Abstract: We propose that biases in attitude and stereotype formation might arise as a result of learned differences in the extent to which social groups have previously been predictive of behavioral or physical properties. Experiments 1 and 2 demonstrate that differences in the experienced predictiveness of groups with respect to evaluatively neutral information influence the extent to which participants later form attitudes and stereotypes about those groups. In contrast, Experiment 3 shows no influence of predictiveness when using a procedure designed to emphasize the use of higher level reasoning processes, a finding consistent with the idea that the root of the predictiveness bias is not in reasoning. Experiments 4 and 5 demonstrate that the predictiveness bias in formation of group beliefs does not depend on participants making global evaluations of groups. These results are discussed in relation to the associative mechanisms proposed by Mackintosh (1975) to explain similar phenomena in animal conditioning and associative learning.
A super low power MICS band receiver front-end down converter on 65 nm CMOS
Publisher: IEEE
Date: 10-2010
A Unifying Framework for Global Regulation via Nonlinear Output Feedback
Publisher: IEEE
Date: 2003
Advantages of smooth trajectory tracking as crane anti-swing schemes
Publisher: IEEE
Date: 02-2009
Rabi resonance in spin systems: Theory and experiment
Publisher: Elsevier BV
Date: 05-2014
DOI: 10.1016/J.JMR.2014.02.014
Abstract: The response of a magnetic resonance spin system is predicted and experimentally verified for the particular case of a continuous wave litude modulated radiofrequency excitation. The experimental results demonstrate phenomena not previously observed in magnetic resonance systems, including a secondary resonance condition when the litude of the excitation equals the modulation frequency. This secondary resonance produces a relatively large steady state magnetisation with Fourier components at harmonics of the modulation frequency. Experiments are in excellent agreement with the theoretical prediction derived from the Bloch equations, which provides a sound theoretical framework for future developments in NMR spectroscopy and imaging.
Probability Steiner trees and maximum parsimony in phylogenetic analysis
Publisher: Springer Science and Business Media LLC
Date: 25-06-2012
DOI: 10.1007/S00285-011-0442-4
Abstract: The phylogenetic tree (PT) problem has been studied by a number of researchers as an application of the Steiner tree problem, a well-known network optimisation problem. Of all the methods developed for phylogenies the maximum parsimony (MP) method is a simple and commonly used method because it relies on directly observable changes in the input nucleotide or amino acid sequences. In this paper we show that the non-uniqueness of the evolutionary pathways in the MP method leads us to consider a new model of PTs. In this so-called probability representation model, for each site a node in a PT is modelled by a probability distribution of nucleotide or amino acid states, and hence the PT at a given site is a probability Steiner tree, i.e. a Steiner tree in a high-dimensional vector space. In spite of the generality of the probability representation model, in this paper we restrict our study to constructing probability phylogenetic trees (PPT) using the parsimony criterion, as well as discussing and comparing our approach with the classical MP method. We show that for a given input set although the optimal topology as well as the total tree length of the PPT is the same as the PT constructed by the classical MP method, the inferred ancestral states and branch lengths are different and the results given by our method provide a plausible alternative to the classical ones.
Managing type 1 diabetes mellitus in ambulatory patients
Publisher: IEEE
Date: 2000
A new approach to adaptive robust control
Publisher: Wiley
Date: 05-1993
On some key issues in the windsurfer approach to adaptive robust control
Publisher: Elsevier BV
Date: 11-1995
A direct adaptive control strategy for managing diabetes mellitus
Publisher: IEEE
Date: 2002
Robustness of Vibrational Control in the Presence of Additive Disturbances
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2022
Bifurcation Effects in Robust Adaptive Control
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-1988
DOI: 10.1109/31.1830
Cross‐Cultural Measurement Invariance of Adolescent Self‐Report on the Pediatric Quality of Life Inventory™ 4.0
Publisher: Wiley
Date: 04-08-2015
DOI: 10.1111/JORA.12218
Consensus only control in DC microgrids
Publisher: ACM
Date: 12-06-2018
Detectability and Uniform Global Asymptotic Stability in Switched Nonlinear Time-Varying Systems
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2020
Solving the bloch equation with periodic excitation using harmonic balancing: Application to Rabi modulated excitation
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2015
Non-local stabilization of a spherical inverted pendulum
Publisher: Informa UK Limited
Date: 07-2008
Stability and active power sharing in droop controlled inverter interfaced microgrids: Effect of clock mismatches
Publisher: Elsevier BV
Date: 07-2018
Personalized Public Transportation: A Mobility Model and its Application to Melbourne
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2015
On modeling and control for a maglev system
Publisher: Elsevier BV
Date: 09-2010
Calibration free upper limb joint motion estimation algorithm with wearable sensors
Publisher: IEEE
Date: 11-2017
Discussion on: A Reduced-Order Controller Design for Nonlinear Systems with Uncertainties and Disturbances
Publisher: Elsevier BV
Date: 06-2004
Centralized control implementation using distributed observer for Meglev systems
Publisher: IEEE
Date: 07-2017
Nonlinear averaging analysis of the incremental pole placement adaptive controller
Publisher: Elsevier BV
Date: 09-1991
An efficient brute-force solution to the network reconfiguration problem
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2000
DOI: 10.1109/61.871365
Effects of robotic exoskeleton dynamics on joint recruitment in a neurorehabilitation context
Publisher: IEEE
Date: 08-2015
Overload prevention and loss minimization in managed distribution networks
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2000
DOI: 10.1109/61.871361
Robust control of uncertain nonlinear systems via measurement feedback
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-1999
DOI: 10.1109/9.754823
On extremum seeking in bioprocesses with multivalued cost functions
Publisher: Wiley
Date: 24-03-2009
DOI: 10.1002/BTPR.87
Abstract: Finding optimal operating modes for bioprocesses has been, for a long time, a relevant issue in bioengineering. The problem is of special interest when it implies the simultaneous optimization of competing objectives. In this paper, we address the problem of finding optimal steady states that achieve the best tradeoff between yield and productivity by using nonmodel-based extremum-seeking control with semiglobal practical stability and convergence properties. A special attention is paid to processes with multiple steady states and multivalued cost functions.
Compatible Formation Set for UAVs with Visual Sensing Constraint
Publisher: IEEE
Date: 06-2018
Probing to Observe Neural Dynamics Investigated with Networked Kuramoto Oscillators
Publisher: World Scientific Pub Co Pte Lt
Date: 08-11-2017
DOI: 10.1142/S0129065716500386
Abstract: The expansion of frontiers in neural engineering is dependent on the ability to track, detect and predict dynamics in neural tissue. Recent innovations to elucidate information from electrical recordings of brain dynamics, such as epileptic seizure prediction, have involved switching to an active probing paradigm using electrically evoked recordings rather than traditional passive measurements. This paper positions the advantage of probing in terms of information extraction, by using a coupled oscillator Kuramoto model to represent brain dynamics. While active probing performs better at observing underlying system synchrony in Kuramoto networks, especially in non-Gaussian measurement environments, the benefits diminish with increasing relative size of electrode spatial resolution compared to synchrony area. This suggests probing will be useful for improved characterization of synchrony for suitably dense electrode recordings.
Learning control in robot-assisted rehabilitation of motor skills–a review
Publisher: Informa UK Limited
Date: 02-01-2016
On robustness analysis of linear vibrational control systems
Publisher: Elsevier BV
Date: 2018
On V-shaped flight formation of bird flocks with visual communication constraints
Publisher: IEEE
Date: 07-2017
Stabilising influence of a synchronous condenser in low inertia networks
Publisher: Institution of Engineering and Technology (IET)
Date: 02-07-2020
Nonlinear energy-based control method for aircraft dynamics
Publisher: IEEE
Date: 2001
Decentralized PID Control Design for Magnetic Levitation Systems Using Extremum Seeking
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2017
Markovian framework for diabetes control
Publisher: IEEE
Date: 2001
PV generation and demand mismatch: Evaluating the potential of residential storage
Publisher: IEEE
Date: 02-2015
On robustness analysis of a vibrational control system: Input-to-state practical stability
Publisher: IEEE
Date: 06-2016
System identification and controller design for dual actuated hard disk drive
Publisher: Elsevier BV
Date: 06-2004
Markov modelling and adaptive control in management of type 1 diabetes mellitus
Publisher: IEEE
Date: 2001
Estimation of noisy quantized random observation coefficient AR time-series
Publisher: IEEE
Date: 1994
Robustness of Nonlinear Vibrational Control Systems based on Sampling Lyapunov Method
Publisher: IEEE
Date: 06-2018
Open-loop discretization methods for control systems design
Publisher: Informa UK Limited
Date: 2001
Towards a smart automated surface irrigation management in rice-growing areas in Italy
Publisher: PAGEPress Publications
Date: 17-02-2017
DOI: 10.4081/JAE.2017.585
Abstract: Italy is the leading rice producer in Europe, accounting for more than half of the total high-quality production of this crop. Rice is traditionally grown in fields that remain flooded starting with crop establishment until close to harvest, and this traditional irrigation technique (i.e., continuous submergence) is recognised as an important water resource sink (almost 40% of the irrigation water available worldwide is used for paddy areas). Meanwhile, the water management in rice areas requires a high level of labour because it is based on maintaining a predetermined water height in paddy fields and because the regulation of input and output flow is typically operated manually by the farmer. This study reveals the hardware and software characteristics of an automated and remote controlled technology tested for the first time in a rice farm near Pavia (Italy), during the 2016 growing season, aiming at a more efficient and less burdensome irrigation management system for rice fields. A water level sensor in the field provides the data required to govern the inflow regulation gate in real-time, according to the precise time to cut off the flow rate. Using a dedicated web page, the farmer can control flows, volumes and water levels in the fields by operating directly on the gate if necessary or setting the irrigation program according to his agronomic practices.
New Trends in Nonlinear Control
Publisher: Elsevier BV
Date: 08-2006
Estimation of Noisy Quantized Gaussian AR Time-series with Randomly Varying Observation Coefficient
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-1995
DOI: 10.1109/78.382419
LMS Estimation via Structural Detection
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 1998
DOI: 10.1109/78.720368
Necessary conditions for stability and attractivity of continuous systems
Publisher: Informa UK Limited
Date: 07-2003
Limiting Behavior of Hybrid Time-Varying Systems
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2022
How exciting can a signal really be?
Publisher: Elsevier BV
Date: 1987
Human motor learning through iterativemodel reference adaptive control
Publisher: Elsevier BV
Date: 2011
Nonlinear estimation of the BOLD signal
Publisher: Elsevier BV
Date: 04-2008
DOI: 10.1016/J.NEUROIMAGE.2007.11.024
Abstract: Signal variations in functional Magnetic Resonance Imaging experiments essentially reflect the vascular system response to increased demand for oxygen caused by neuronal activity, termed the blood oxygenation level dependent (BOLD) effect. The most comprehensive model to date of the BOLD signal is formulated as a mixed continuous-discrete-time system of nonlinear stochastic differential equations. Previous approaches to the analysis of this system have been based on linearised approximations of the dynamics, which are limited in their ability to capture the inherent nonlinearities in the physiological system. In this paper we present a nonlinear filtering method for simultaneous estimation of the hidden physiological states and the system parameters, based on an iterative coordinate descent framework. State estimates of the cerebral blood flow, cerebral blood volume and deoxyhaemoglobin content are determined using a particle filter, demonstrated via simulation to be accurate, robust and efficient in comparison to linearisation-based techniques. The adaptive state and parameter estimation algorithm generates physiologically reasonable parameter estimates for experimental fMRI data. It is anticipated that signal processing techniques for modelling and estimation will become increasingly important in fMRI analyses as limitations of linear and linearised modelling are reached.
The importance of spatial distribution when analysing the impact of electric vehicles on voltage stability in distribution networks
Publisher: Springer Science and Business Media LLC
Date: 22-04-2014
A distributed electric vehicle charging management algorithm using only local measurements
Publisher: IEEE
Date: 02-2014
The dynamics of the epileptic brain reveal long memory processes
Publisher: Frontiers Media SA
Date: 24-10-2014
Event Triggered Adaptive Differential Modulation: A New Method for Traffic Reduction in Networked Control Systems
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2013
Iterative identification and two step control design for partially unknown unstable plants
Publisher: Informa UK Limited
Date: 2001
An Algorithm to Find Common Zeroing-Output Systems of Arbitrarily Switched Linear Time-Invariant Systems
Publisher: Elsevier BV
Date: 07-2017
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