Bayesian inference for complex regression models using mixtures. The project will use mixtures to flexibly model complex regression functions and will develop Bayesian methods for carrying out statistical inference on these models. The models will deal with both Gaussian and non-Gaussian data. Multiple explanatory variables are dealt with by mixing simple additives to produce flexible high dimensional function estimates. Variable selection and model averaging will be used to identify important v ....Bayesian inference for complex regression models using mixtures. The project will use mixtures to flexibly model complex regression functions and will develop Bayesian methods for carrying out statistical inference on these models. The models will deal with both Gaussian and non-Gaussian data. Multiple explanatory variables are dealt with by mixing simple additives to produce flexible high dimensional function estimates. Variable selection and model averaging will be used to identify important variables and thus make the estimation more efficient. The methods will be extended to multivariate responses where account will taken be taken of the structure of the dependence between responses.Read moreRead less
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
High-performance computational data-mining techniques for feature detection in complex time series from large-scale, networked plasma experiments. Terabytes of data are gathered from large experimental facilities as complex time-series. Analysis of these data is daunting, especially when they involve high-dimensional spectral or image arrays. We will develop high-performance computational techniques for dimension reduction, efficient data-mining, and experimental control, using as an initial ta ....High-performance computational data-mining techniques for feature detection in complex time series from large-scale, networked plasma experiments. Terabytes of data are gathered from large experimental facilities as complex time-series. Analysis of these data is daunting, especially when they involve high-dimensional spectral or image arrays. We will develop high-performance computational techniques for dimension reduction, efficient data-mining, and experimental control, using as an initial target the H-1NF plasma fusion MNRF at the ANU and its >100 GB/year data stream. The techniques will immediately provide Australian researchers with unique tools for collaboration in international research to develop fusion as a low-emissions source of electricity, and will be applicable to complex time-series analysis in other areas of science, medicine, and defence.Read moreRead less
Modelling and estimation methods for discrete multi-dimensional systems. Multi-dimensional signal processing plays a role in a variety of application areas, ranging from remote sensing for environmental monitoring and geological mapping, to medical imaging and the automatic control of industrial processes. The success of the project will provide mathematical tools for the advancement of the state-of-the-art in these broad areas.
Signal Concentration, Robust Signal Processing and Information Theory on the Unit Sphere. This project will assist Australia in maintaining and elevating its international research role in the development of breakthrough signal processing techniques applied to mobile communication, geodesy, astronomy, defence and surveillance, and acoustic modeling of human hearing. The project's high impact contributions will advance Australia's knowledge base and through its applications attract industry inte ....Signal Concentration, Robust Signal Processing and Information Theory on the Unit Sphere. This project will assist Australia in maintaining and elevating its international research role in the development of breakthrough signal processing techniques applied to mobile communication, geodesy, astronomy, defence and surveillance, and acoustic modeling of human hearing. The project's high impact contributions will advance Australia's knowledge base and through its applications attract industry interest particularly in the development of improved instrumentation. The publication of outcomes will elevate Australia's research reputation. The project provides high quality research training for gifted postgraduate students and postdoctoral researchers.Read moreRead less
A Computational Study of Nonconvex and Nonlinear Semi-infinite Optimisation Problems in Signal Processing. The operation of filtering is an important part of most modern communication engineering systems. Many important problems, which arise naturally from communications engineering applications, can be formulated as nonconvex optimization problems and nonlinear semi-infinite and/or semi-definite optimization problems. New optimization theory, in combination with novel computationally efficient ....A Computational Study of Nonconvex and Nonlinear Semi-infinite Optimisation Problems in Signal Processing. The operation of filtering is an important part of most modern communication engineering systems. Many important problems, which arise naturally from communications engineering applications, can be formulated as nonconvex optimization problems and nonlinear semi-infinite and/or semi-definite optimization problems. New optimization theory, in combination with novel computationally efficient solution methods, and efficient hardware implementation will be developed. The outcomes will enhance Australia's reputation in this cutting edge research and facilitate opportunity for international collaboration as well as commercial opportunity. The project will also provide an excellent environment for the training of junior researchers in the area.Read moreRead less
Feedback Architectures with Parallel Communication Channels. Feedback control is an enabling, though often hidden, technology. For example, without control loops, cars, mining and manufacturing plants cannot operate in an efficient and safe manner. To reduce costs, there has been a trend to use general purpose communication systems, such as WiFi, for feedback control. These communication systems have only limited capacity and reliability. This can lead to performance degradation and system failu ....Feedback Architectures with Parallel Communication Channels. Feedback control is an enabling, though often hidden, technology. For example, without control loops, cars, mining and manufacturing plants cannot operate in an efficient and safe manner. To reduce costs, there has been a trend to use general purpose communication systems, such as WiFi, for feedback control. These communication systems have only limited capacity and reliability. This can lead to performance degradation and system failure. The current project aims at proposing novel robust networked control system architectures. Our results will be useful to allow industries to use standard communications technology for control, thus, alleviating costs associated with developing dedicated application specific communication infrastructure.Read moreRead less
New perspectives on computing methods for mathematical signal processing. This project determines how best to design computing methods for challenging demands in signal processing. The expected conceptual & algorithmic advances will have significant repercussions in a number of fields including optimal filtering theory and will contribute to applications ranging from bio-informatics to electrical engineering. The new techniques will allow development of software that will benefit Australian in ....New perspectives on computing methods for mathematical signal processing. This project determines how best to design computing methods for challenging demands in signal processing. The expected conceptual & algorithmic advances will have significant repercussions in a number of fields including optimal filtering theory and will contribute to applications ranging from bio-informatics to electrical engineering. The new techniques will allow development of software that will benefit Australian industries and technologies. The formation of a strong research team across four universities in Australia, USA and Japan will enhance our scientific standing in the international community and will place Australian researchers at the forefront of world-class research methods. Read moreRead less
The Time-Varying Eigenvalue Problem with Application to Signal Processing and Control. Linear models are ubiquitous in representing physical processes. Decomposing a linear model into its fundamental components is known as the eigenvalue problem. In applications as wide ranging as astronomy, aircraft control systems, Internet search engines and communication systems, it is necessary to perform this decomposition of a pertinent time varying linear model on the fly. This project aims to develop si ....The Time-Varying Eigenvalue Problem with Application to Signal Processing and Control. Linear models are ubiquitous in representing physical processes. Decomposing a linear model into its fundamental components is known as the eigenvalue problem. In applications as wide ranging as astronomy, aircraft control systems, Internet search engines and communication systems, it is necessary to perform this decomposition of a pertinent time varying linear model on the fly. This project aims to develop significantly faster and more accurate algorithms for this time varying eigenvalue problem than currently exist. Very modern techniques will be employed to achieve this aim, and the potential benefits to Australian hi-tech industries are great.
Read moreRead less
Fundamental Studies in System Identification. To operate a dynamic system such as a chemical process plant or an economy one needs two things; the equations describing the system; a way of regulating the system to provide desired outcomes. System identification provides the first; control engineering design provides the second. This proposal addresses three important problems in system identification and control. Firstly since the equations can never be known precisely we aim to determine what i ....Fundamental Studies in System Identification. To operate a dynamic system such as a chemical process plant or an economy one needs two things; the equations describing the system; a way of regulating the system to provide desired outcomes. System identification provides the first; control engineering design provides the second. This proposal addresses three important problems in system identification and control. Firstly since the equations can never be known precisely we aim to determine what is the best one can do? Secondly to provide then tight error bounds for the control design;
thirdly to develop new methods for some hitherto unresolved problems in system identification.Read moreRead less