Joint System Identification for Point Processes and Time-series. In various application areas such as neurophysiology, earthquake modeling, price spikes in electricity markets, the data of interest are point processes (aka sequences of events) or combinations of point processes and analog signals. To understand the underlying subject of interest we need to be able to extract the maximum information from these observation sequences. The current tools for doing this are very limited. This resear ....Joint System Identification for Point Processes and Time-series. In various application areas such as neurophysiology, earthquake modeling, price spikes in electricity markets, the data of interest are point processes (aka sequences of events) or combinations of point processes and analog signals. To understand the underlying subject of interest we need to be able to extract the maximum information from these observation sequences. The current tools for doing this are very limited. This research program will develop the complex signal processing and system methodology needed to create a suitable tool set.Read moreRead less
A Bayesian framework for frequency domain identification. The national and social benefits of the project will be reflected
through the application recognition of the research work in the various industry and research community; and also through our international collaboration. The national and social benefits are also delivered by producing specialized researchers and engineers in systems and control engineering. These people include the research students who will participate in and learn f ....A Bayesian framework for frequency domain identification. The national and social benefits of the project will be reflected
through the application recognition of the research work in the various industry and research community; and also through our international collaboration. The national and social benefits are also delivered by producing specialized researchers and engineers in systems and control engineering. These people include the research students who will participate in and learn from the proposed project.Read moreRead less
Estimation and Control of Noisy Riemannian Systems. Many application areas such as satellite control, computer vision, coordination of rigid bodies, require the estimation and control of systems subject to geometric constraints. Most current algorithms for doing this are deterministic and can fail catastrophically in the presence of noise. This project aims to provide:
(i) Methods for analysing and then redesigning deterministic algorithms to ensure stability in the presence of noise;
(ii) New ....Estimation and Control of Noisy Riemannian Systems. Many application areas such as satellite control, computer vision, coordination of rigid bodies, require the estimation and control of systems subject to geometric constraints. Most current algorithms for doing this are deterministic and can fail catastrophically in the presence of noise. This project aims to provide:
(i) Methods for analysing and then redesigning deterministic algorithms to ensure stability in the presence of noise;
(ii) New design methods that deal with noise in an optimal way;
(iii) Noise resistant methods for distributed consensus seeking systems and cooperative control systems.
The outcomes will advance and benefit spatio-temporal data analysis and coordination in areas such as transport, health and video-security.Read moreRead less
Point processes system identification under simultaneity. Neuroscientists study neuronal brain dynamics of mammals via recordings from scores of tiny electrodes. But analysing these experiments is a problem because current methods cannot handle the common case where neurons discharge simultaneously. This project aims to provide powerful new tools to overcome this bottleneck.
Riemannian System Identification. A growing number of applications such as satellite attitude estimation, pose estimation in computer vision and direction estimation in statistics require the study of random processes in Riemannian manifolds and Lie Groups. This project will provide: methods for the construction/ numerical simulation of such processes; methods of system identification and their asymptotic performance analysis; and, algorithms for process state estimation.
Modeling stochastic systems in Riemannian manifolds. This project aims to develop new statistical signal processing and control engineering algorithms and tools that will enable tracking of objects remotely on land and in space. A growing number of applications require the study of random processes in Riemannian manifolds, that is processes that evolve subject to a geometric constraint. This project aims to provide methods for the numerical simulation of such processes, methods of online and off ....Modeling stochastic systems in Riemannian manifolds. This project aims to develop new statistical signal processing and control engineering algorithms and tools that will enable tracking of objects remotely on land and in space. A growing number of applications require the study of random processes in Riemannian manifolds, that is processes that evolve subject to a geometric constraint. This project aims to provide methods for the numerical simulation of such processes, methods of online and offline system identification from data on such processes and asymptotic performance analysis; and algorithms for process state estimation that obeys the geometry. The outcomes will advance and benefit spatio-temporal data analysis in areas such as transport, health and video-security.Read moreRead less
Vector network system identification. This machine learning project aims to provide more reliable ways to identify the structure and function of dynamic networks from both continuous and discrete network data. The project will use all the data and create principled new metrics. This could enable early diagnosis of network faults across a range of applications for example in power systems or diseased human brains. It could also enable discovery of critical functional subnetworks affecting reliabl ....Vector network system identification. This machine learning project aims to provide more reliable ways to identify the structure and function of dynamic networks from both continuous and discrete network data. The project will use all the data and create principled new metrics. This could enable early diagnosis of network faults across a range of applications for example in power systems or diseased human brains. It could also enable discovery of critical functional subnetworks affecting reliable operation in large complex human systems (such as financial systems) or natural systems (such as gene regulatory networks).Read moreRead less
A unified framework for analyzing the timescale of interest for traffic measurements, modelling and performance analysis. The revenue generated from traditional telecommunication services is continuing to drop. New value-added services such as multimedia services become the fastest growing revenue-generating sector in Australia's telecommunications industry. The ubiquitous presence of scaling behaviour in network traffic presents a big challenge for delivering better Quality-of-Service (QoS) whi ....A unified framework for analyzing the timescale of interest for traffic measurements, modelling and performance analysis. The revenue generated from traditional telecommunication services is continuing to drop. New value-added services such as multimedia services become the fastest growing revenue-generating sector in Australia's telecommunications industry. The ubiquitous presence of scaling behaviour in network traffic presents a big challenge for delivering better Quality-of-Service (QoS) which is demanded by the new services. A complete understanding of the scaling behaviour and its impact is very important. This research addresses a key problem of defining the timescale range of interest for the scaling behaviour. The research outcome benefits a number of areas, which are all critical for developing enhanced QoS support and better network management.Read moreRead less
Convex optimisation for control, signal processing and communication systems. Renewable control of complex systems, signal processing, telecommunication and in general any industries interested in these applications stand to benefit from our research. In particular, the automotive and defence industries stand to benefit from the nonlinear control design aspect of the proposed project outcomes. The
telecommunications industries, on the other hand, benefit from the signal processing and communicat ....Convex optimisation for control, signal processing and communication systems. Renewable control of complex systems, signal processing, telecommunication and in general any industries interested in these applications stand to benefit from our research. In particular, the automotive and defence industries stand to benefit from the nonlinear control design aspect of the proposed project outcomes. The
telecommunications industries, on the other hand, benefit from the signal processing and communications aspects. We also build a core expertise in optimisation and its applications in Australia by training PhD students and Postdoctoral researchers. The research collaborations will cement and maintain the international linkages which will improve applied research in AustraliaRead moreRead less
Fundamentals of active sensor network for damage identification in engineering structures. The development of active sensor network techniques for Australia's vast civil and defence infrastructure will improve operational safety, reduce maintenance costs and extend the residual life of many of our engineered assets. The resulting cost-efficiencies will advantage Australian producers in competitive global markets; our companies will be well placed to produce and install active sensor network tech ....Fundamentals of active sensor network for damage identification in engineering structures. The development of active sensor network techniques for Australia's vast civil and defence infrastructure will improve operational safety, reduce maintenance costs and extend the residual life of many of our engineered assets. The resulting cost-efficiencies will advantage Australian producers in competitive global markets; our companies will be well placed to produce and install active sensor network techniques and to provide training in the associated asset management systems. Australian industry will have a unique opportunity to collaborate with the world-class research networks on emerging areas such as damage diagnosis, prognosis and control, and structural repair.Read moreRead less