Electronic Auditory Pathway. We will develop electronic building blocks to investigate biological signal processing. In particular, we will investigate the auditory pathway and develop the most accurate electronic model of the biological cochlea and auditory nerve. These will be followed by electronic circuits that model the processing of sensory signals in the brain. Processing signals with neural spikes offers distinct advantages over current analogue and digital signal processing techniques i ....Electronic Auditory Pathway. We will develop electronic building blocks to investigate biological signal processing. In particular, we will investigate the auditory pathway and develop the most accurate electronic model of the biological cochlea and auditory nerve. These will be followed by electronic circuits that model the processing of sensory signals in the brain. Processing signals with neural spikes offers distinct advantages over current analogue and digital signal processing techniques in terms of noise, energy consumption and extraction of temporal information. We will implement the first spike-based models of pitch and timbre perception, and a neural model of speech recognition in noisy environments.Read moreRead less
Online Structural Health Monitoring (SHM) System Using Active Diagnostic Sensor Network. It is imperative to remain technological leading for Australian research community. But current lack of reliable technique in structural health monitoring in Australia is considerably impeding her competition with other developed countries in areas of forefront technology. Outcomes of the project will lead to an online structural health monitoring system incorporated with active diagnostic sensor network, re ....Online Structural Health Monitoring (SHM) System Using Active Diagnostic Sensor Network. It is imperative to remain technological leading for Australian research community. But current lack of reliable technique in structural health monitoring in Australia is considerably impeding her competition with other developed countries in areas of forefront technology. Outcomes of the project will lead to an online structural health monitoring system incorporated with active diagnostic sensor network, related software and hardware, novel signal processing technique, and artificial intelligence algorithm-based damage identification scheme. Its successful applications in various industries, e.g. aerospace, maritime and civil, are expected to bring significant improvement in operation safety and great benefit in reducing maintenance cost.Read moreRead less
Vector quantization approaches to nonlinear stochastic estimation. Many problems in health, economics, telecommunications and industrial control can be formulated as estimation problems with uncertain data. This project is aimed at developing a novel class of algorithms aimed at high complexity estimation problems. If successful, the project will provide new approaches to these problems.
Joint modelling and recognition of linguistic and paralinguistic speech information. A new modelling framework will be developed exploiting interdependence between linguistic and paralinguistic cues to improve automatic recognition of emotion-related information. Applications in the high-tech industry include automatic routing of angry telephone customers or pre-suicidal crisis centre callers to specialist operators/clinicians.
Automated Diagnosis of Faults in Rotating Machinery using Adaptive Network Based Fuzzy Inference. The long-term integrity of engineering assets depends on the quality of their maintenance which runs into billions of dollars per year in Australia. This project aims to develop a new fundamental automated technique for the detection and diagnosis of machinery faults. The innovation lies in the ability of this technique to not depend on knowledge of fault components in the discrete wavelet packet ....Automated Diagnosis of Faults in Rotating Machinery using Adaptive Network Based Fuzzy Inference. The long-term integrity of engineering assets depends on the quality of their maintenance which runs into billions of dollars per year in Australia. This project aims to develop a new fundamental automated technique for the detection and diagnosis of machinery faults. The innovation lies in the ability of this technique to not depend on knowledge of fault components in the discrete wavelet packet analysis. All other work conducted to date depends on knowledge of these components and their location. The results of this work will vastly improve the costly manually based diagnostics procedures in the maintenance of plant and industrial assets.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE120102210
Funder
Australian Research Council
Funding Amount
$350,333.00
Summary
Feedback control as a tool for enhanced neuroprosthetic stimulation. The aim is to use control theory tools to find optimal stimulation parameters to use in a bionic implant. This project will lead to improvements in understanding of mechanisms underlying electrical stimulation and to improvements in medical bionics technologies.
Continuous wave excitation for low power Magnetic Resonance Imaging. This project aims to augment the capabilities of Magnetic Resonance Imaging (MRI) systems, using continuous wave (CW) transmission and signal reception, to image objects using very low excitation power. Any given MRI sequence tries to solve an inverse problem, involving estimation of some subset of hidden states and parameters of the system, given the observed data. Using transient and steady-state CW magnetisation dynamics to ....Continuous wave excitation for low power Magnetic Resonance Imaging. This project aims to augment the capabilities of Magnetic Resonance Imaging (MRI) systems, using continuous wave (CW) transmission and signal reception, to image objects using very low excitation power. Any given MRI sequence tries to solve an inverse problem, involving estimation of some subset of hidden states and parameters of the system, given the observed data. Using transient and steady-state CW magnetisation dynamics to solve inverse problems is expected to advance technology toward lower power, lower cost solutions for MRI scanners in healthcare and industrial applications, including materials science and mineral processing.Read moreRead less
New entropy measures of short term signals for smart wearable devices. This project aims to improve reliability and accuracy of wearable devices by developing a new set of computationally efficient algorithms. Wearable devices can be very effective in remote and continuous monitoring to detect short or bursty anomalous events. Present devices are unable to detect such events effectively due to limited capability in processing short length signal. This project will provide computationally efficie ....New entropy measures of short term signals for smart wearable devices. This project aims to improve reliability and accuracy of wearable devices by developing a new set of computationally efficient algorithms. Wearable devices can be very effective in remote and continuous monitoring to detect short or bursty anomalous events. Present devices are unable to detect such events effectively due to limited capability in processing short length signal. This project will provide computationally efficient algorithms for signal quality analysis and enhanced feature extraction methods in resource constrained wearable devices. This will improve the reliability and performance of wearable devices for adoption in intelligent decision-making systems.Read moreRead less
Analysing Iterative Machine Learning Algorithms with Information Geometric Methods. Online machine learning problems arise from situations where data is provided a point at a time. There are many classical algorithms for solving such problems based on the principle of stochastic gradient descent. Recent research by the CIs and others have thrown up interesting but diverse geometric connections that offer new insights. The proposed research aims to integrate the understanding of these algori ....Analysing Iterative Machine Learning Algorithms with Information Geometric Methods. Online machine learning problems arise from situations where data is provided a point at a time. There are many classical algorithms for solving such problems based on the principle of stochastic gradient descent. Recent research by the CIs and others have thrown up interesting but diverse geometric connections that offer new insights. The proposed research aims to integrate the understanding of these algorithms with the aim of designing algorithms better able to exploit prior knowledge, and to extend existing algorithms to new problem domains thus offering well principled and well understood algorithms for solving a variety of novel online problems.Read moreRead less
Modelling of neural plasticity for enhanced performance of brain-machine interfaces. Plasticity of the brain is one of the great scientific challenges of neuroscience. The aim of this project is to model the synaptic changes that occur with reward-modulated spike-timing-dependent plasticity and apply the model to developing plasticity targeted brain-machine interfaces. The significance of this approach is that such plasticity targeted techniques provide the prospect of taking advantage of the un ....Modelling of neural plasticity for enhanced performance of brain-machine interfaces. Plasticity of the brain is one of the great scientific challenges of neuroscience. The aim of this project is to model the synaptic changes that occur with reward-modulated spike-timing-dependent plasticity and apply the model to developing plasticity targeted brain-machine interfaces. The significance of this approach is that such plasticity targeted techniques provide the prospect of taking advantage of the underlying neural plasticity to optimise the form of the neural recording and electrical stimulation. The outcomes will be to greatly improve the performance of brain-machine interface in terms of measures such as the number and sensitivity of channels, as well as robustness and reliability.Read moreRead less