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
Model-Reduction Techniques for Control, Communication and Circuits. Model reduction is an important area of study in the analysis and design of dynamical systems. Its objective is to obtain a low-order model given a high-order system model such that the low-order model closely approximates the input-output behaviour of the original high-order system. Although theory and application of model reduction is well developed, there are many unresolved issues such as efficient model reduction techniq ....Model-Reduction Techniques for Control, Communication and Circuits. Model reduction is an important area of study in the analysis and design of dynamical systems. Its objective is to obtain a low-order model given a high-order system model such that the low-order model closely approximates the input-output behaviour of the original high-order system. Although theory and application of model reduction is well developed, there are many unresolved issues such as efficient model reduction techniques for large-scale circuit simulation and communication applications, frequency-weighted model reduction techniques for controller-design applications, and error bounds for the reduction techniques. The project aims to address these issues.Read moreRead less
Mathematical modelling of information flow in social networks. This proposal aims to develop new mathematical and statistical methods to understand information flow in social networks. By using novel information theoretic techniques, it will create new methods to characterise social information flow in social networks. These tools will allow derivation of fundamental limits of predictability for AI methods applied to digital data. New mathematics of information flow will produce insights into so ....Mathematical modelling of information flow in social networks. This proposal aims to develop new mathematical and statistical methods to understand information flow in social networks. By using novel information theoretic techniques, it will create new methods to characterise social information flow in social networks. These tools will allow derivation of fundamental limits of predictability for AI methods applied to digital data. New mathematics of information flow will produce insights into social influence in online social networks. Benefits include: better understanding of how echo chambers may form in social networks, predictive models for how misinformation can spread online such as during an emergency, and a framework for intercomparison of AI methods applied to digital data on individuals. Read moreRead less