Scheduling and quality of service in Long Term Evolution telecommunications. There is an explosion of mobile telecommunications with over 50 billion connections expected by 2020. The next generation of mobile broadband will be based on a new technology known as Long Term Evolution (LTE) and, in this context, the goal of this project is to improve the efficiency of these systems by developing new techniques for scheduling.
Automated vision-based aircraft collision warning technologies. Australia is a sparsely populated country with a number of unique airspace features. This project will investigate novel vision-based collision warning systems that can improve safety for piloted aircraft and also help achieve integration of UASs (Uninhabited Aerial Systems) into national airspace. The benefits of UAS technologies are particularly relevant to Australia, as governments and industry struggle to cope with providing equ ....Automated vision-based aircraft collision warning technologies. Australia is a sparsely populated country with a number of unique airspace features. This project will investigate novel vision-based collision warning systems that can improve safety for piloted aircraft and also help achieve integration of UASs (Uninhabited Aerial Systems) into national airspace. The benefits of UAS technologies are particularly relevant to Australia, as governments and industry struggle to cope with providing equivalent levels of service to remote communities over vast distances (or border protection of vast regions). The population base of Australia requires that cost-effective solutions are sought to meet this end. 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
Automatic control systems for low-energy pipelines in irrigation networks. Automatic control systems for low-energy pipelines in irrigation networks. This project aims to design automated pipelines to distribute irrigation water from backbone open-channels to end-users. Automation can make irrigation networks more efficient, which is important for food security and the environment. Automation is expected to achieve low-energy distribution, in line with the gravity-powered operation of typical op ....Automatic control systems for low-energy pipelines in irrigation networks. Automatic control systems for low-energy pipelines in irrigation networks. This project aims to design automated pipelines to distribute irrigation water from backbone open-channels to end-users. Automation can make irrigation networks more efficient, which is important for food security and the environment. Automation is expected to achieve low-energy distribution, in line with the gravity-powered operation of typical open-channel networks. The main challenges are the development of suitable models for designing outlet-flow control systems, optimization-based outlet-flow scheduling methods for ensuring operation within hydraulic constraints, and system monitoring techniques. This project will design automatic control systems to enable low-energy water distribution from open-channels to end-users by pipes.Read moreRead less
DC optimisation based synthesis of systems in control, signal processing and wireless communication network. The conceptual advances with new optimisation based solvers to be developed in the area of control, signal processing and wireless communication. Major benefits of this project will be its direct applications to renewable technologies in automobile, health care, digital and communication network industries.
Distributed signal processing and control in sensor networks. Distributed sensor networks find wide applications in smart electricity grids, traffic systems, industrial plants and security systems. Massive amounts of data need be collected, transmitted and processed. This project aims to develop advanced techniques for the monitoring, diagnosis and control for these networks.
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.