Novel time-frequency techniques for analysing and modeling non-stationary physical and engineering data. This project addresses an issue of fundamental importance in science and technology, where non-stationary data (which have time-varying statistics) are ubiquitous. Therefore, the development of time-frequency tools to model and analyse non-stationary data has great potential for impact in a wide range of areas reaching from seismic data analysis to biomedical signal processing to sonar and ra ....Novel time-frequency techniques for analysing and modeling non-stationary physical and engineering data. This project addresses an issue of fundamental importance in science and technology, where non-stationary data (which have time-varying statistics) are ubiquitous. Therefore, the development of time-frequency tools to model and analyse non-stationary data has great potential for impact in a wide range of areas reaching from seismic data analysis to biomedical signal processing to sonar and radar. Employing techniques to be developed in this proposal, we expect to be able to classify and detect features of non-stationary data that were unrecognisable using hitherto known methods.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
Space-time and time-frequency applications of improper complex processes. This project addresses an issue of fundamental importance to many areas in science and engineering. It is thus expected that the results will be disseminated in high-quality journals and receive widespread attention and recognition. This will advance Australia's research profile in the world.
The project can also be expected to have an immediate impact on the design of next generation communications technologies, thus aid ....Space-time and time-frequency applications of improper complex processes. This project addresses an issue of fundamental importance to many areas in science and engineering. It is thus expected that the results will be disseminated in high-quality journals and receive widespread attention and recognition. This will advance Australia's research profile in the world.
The project can also be expected to have an immediate impact on the design of next generation communications technologies, thus aiding Australian industries in the development of frontier technologies.
Australia will also benefit economically and socially by the specialised engineers and researchers in signal processing and communications that will be trained in the course of this project.Read moreRead less
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
Individualized cochlear implant sound coding: Optimized algorithms for better hearing. One in six Australians is affected by hearing loss. Hearing loss impacts on a person's educational and employment opportunities, resulting in a significant economic impact upon Australia. Over 10% of people with hearing impairment have a severe or profound hearing loss and may be candidates for a cochlear implant. Current cochlear implant sound processing only offers limited benefit to users. This project repr ....Individualized cochlear implant sound coding: Optimized algorithms for better hearing. One in six Australians is affected by hearing loss. Hearing loss impacts on a person's educational and employment opportunities, resulting in a significant economic impact upon Australia. Over 10% of people with hearing impairment have a severe or profound hearing loss and may be candidates for a cochlear implant. Current cochlear implant sound processing only offers limited benefit to users. This project represents a truly innovative pathway forward in the development of cochlear implant sound coding that could substantially increase the speech perception of users, enabling these people to become and remain active and productive members of our community.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
Discovery Early Career Researcher Award - Grant ID: DE130101000
Funder
Australian Research Council
Funding Amount
$270,847.00
Summary
Next generation acoustic sensor arrays for super resolution imaging. This project aims to develop a new type of acoustic lens that enhances incoherent sensing. This compressive acoustic sensing approach will achieve super-resolution imaging that is robust to noise. The technology has diverse applications including medical imaging, petroleum prospecting, sonar and acoustic holography and will lead to new technology for Australia.
New Model Predictive Control Design Methods. Automatic computer control is fundamental to sustaining a wide range of manufacturing, mineral processing, chemical processing, and other industries vital to the Australian economy. Furthermore, the efficiency, profitability, and environmental impact of these operations is directly linked to the quality of this computer control. In many situations, even a few percent improvement in automatic control delivers dividends measured in many millions of doll ....New Model Predictive Control Design Methods. Automatic computer control is fundamental to sustaining a wide range of manufacturing, mineral processing, chemical processing, and other industries vital to the Australian economy. Furthermore, the efficiency, profitability, and environmental impact of these operations is directly linked to the quality of this computer control. In many situations, even a few percent improvement in automatic control delivers dividends measured in many millions of dollars. This project will develop design tools allowing for more sophisticated, high performance control to be more widely employed. This will deliver the potential for economic and environmental benefits and energy savings to be achieved across a range of industries.Read moreRead less
Physiologically accurate audio processing in cochlear implants. This project proposes to use a physiologically motivated computational model of the cochlea, which along with newly developed cochlear-implant electrode technology will produce the next quantum improvement in speech intelligibility and quality of hearing for implant recipients.
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