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Research Topic : combined modality
Field of Research : Optimisation
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  • Researchers (18)
  • Funded Activities (5)
  • Organisations (14)
  • Funded Activity

    Discovery Projects - Grant ID: DP0345215

    Funder
    Australian Research Council
    Funding Amount
    $270,000.00
    Summary
    Stochastic Geometry for Multi-sensor Data Fusion System. The aim of this project is to develop efficient algorithms for tracking and sensor management in a multi-sensor multi-target environment. Finite random set theory provides a natural way of representing a random number of (random) object states, an issue that has been largely ignored in the tracking literature until recently. Although a satisfactory foundation for multiple object filtering has been provided by random set theory, in this ear .... Stochastic Geometry for Multi-sensor Data Fusion System. The aim of this project is to develop efficient algorithms for tracking and sensor management in a multi-sensor multi-target environment. Finite random set theory provides a natural way of representing a random number of (random) object states, an issue that has been largely ignored in the tracking literature until recently. Although a satisfactory foundation for multiple object filtering has been provided by random set theory, in this early stage no algorithm capable of tracking many targets has emerged from this framework. We are confident that efficient algorithms can be developed by exploiting the insights and mathematical tools of stochastic geometry
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    Funded Activity

    Discovery Projects - Grant ID: DP0878269

    Funder
    Australian Research Council
    Funding Amount
    $763,000.00
    Summary
    Information Geometry and Compressive Sensing for Radar and Communications. Australia's vast distances, thin population and extensive sea approaches force us to place heavy reliance on telecommunications and the remote sensing that radar and other modalities can provide. This project will enchance capabilities in sensing to provide more reliable, robust and cost effective communications and surveillance over a wide area.
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    Funded Activity

    Research Networks - Grant ID: RN0459979

    Funder
    Australian Research Council
    Funding Amount
    $2,250,000.00
    Summary
    ARC Research Network on Intelligent Sensors, Sensor Networks and Information Processing. Sensor networks, a collection of diverse sensors interconnected via an ad-hoc communication network, are identified as one of the key technologies that over the next two decades will change the way we live. This research network brings together an interdisciplinary team of outstanding Australian researchers representing all the key disciplines required to successfully deploy sensor networks and links this te .... ARC Research Network on Intelligent Sensors, Sensor Networks and Information Processing. Sensor networks, a collection of diverse sensors interconnected via an ad-hoc communication network, are identified as one of the key technologies that over the next two decades will change the way we live. This research network brings together an interdisciplinary team of outstanding Australian researchers representing all the key disciplines required to successfully deploy sensor networks and links this team with the foremost international authorities and leading industry players in the area of sensor networks. This research network will guide collaborative research that will ensure Australia to play a world leading role in sensor network development and implementation.
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    Funded Activity

    Discovery Projects - Grant ID: DP0877483

    Funder
    Australian Research Council
    Funding Amount
    $250,000.00
    Summary
    Optimal Deployment of Wireless Sensor Networks. Wireless sensor networks consist of coordinated sensing devices that offer us new ways to understand and interact with the physical world. Australia is a leading player in developing such networks. For a given technology, the key to both optimising the quality of area monitoring and minimising the cost of a sensor network lies in deciding how best to deploy the sensors. We aim to develop powerful new methods to get the best performance from a plann .... Optimal Deployment of Wireless Sensor Networks. Wireless sensor networks consist of coordinated sensing devices that offer us new ways to understand and interact with the physical world. Australia is a leading player in developing such networks. For a given technology, the key to both optimising the quality of area monitoring and minimising the cost of a sensor network lies in deciding how best to deploy the sensors. We aim to develop powerful new methods to get the best performance from a planned sensor network. This will enhance Australia's research role in this area and directly benefit applications such as national security and environmental monitoring.
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    Funded Activity

    Discovery Projects - Grant ID: DP0343028

    Funder
    Australian Research Council
    Funding Amount
    $172,536.00
    Summary
    New Analytical Perspectives on the Algorithmic Complexity of the Hamiltonian Cycle Problem. Hamiltonian Cycle Problem (HCP), known - in the complexity theory of algorithms -to be NP-hard is proposed for study, from three innovative, separate (yet related) analytical perspectives: singularly perturbed (controlled) Markov chains, that links the HCP with systems and control theories; parametric nonconvex optimization, that links HCP with fast interior point methods of modern optimization an .... New Analytical Perspectives on the Algorithmic Complexity of the Hamiltonian Cycle Problem. Hamiltonian Cycle Problem (HCP), known - in the complexity theory of algorithms -to be NP-hard is proposed for study, from three innovative, separate (yet related) analytical perspectives: singularly perturbed (controlled) Markov chains, that links the HCP with systems and control theories; parametric nonconvex optimization, that links HCP with fast interior point methods of modern optimization and the spectral approach based on a novel adaptation of Ihara-Selberg trace formula for regular graphs. Our mathematical approach to this archetypal complex problem of graph theory and discrete optimization promises to enhance the fundamental understanding - and ultimate "managibility" - of the underlying difficulty of HCP.
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