A lossy compression paradigm for sensory neural coding. By applying new interdisciplinary theoretical results, this research aims to enhance our understanding of how the ear turns sounds into electrical signals in the presence of high levels of random noise. Socio-economic benefits to Australia include: (i) contributions to the knowledge base of theoretical neuroscience, and communications systems, enhancing Australia's reputation for cutting-edge research; (ii) strengthening of European interna ....A lossy compression paradigm for sensory neural coding. By applying new interdisciplinary theoretical results, this research aims to enhance our understanding of how the ear turns sounds into electrical signals in the presence of high levels of random noise. Socio-economic benefits to Australia include: (i) contributions to the knowledge base of theoretical neuroscience, and communications systems, enhancing Australia's reputation for cutting-edge research; (ii) strengthening of European international collaborations; (iii) outcomes that will ultimately impact on improved designs for bionic ears and future biomedical prosthetics; and (iv) commercialisation and technology transfer opportunities, via the transfer of results to wireless artificial sensor networks.Read moreRead less
Collision Avoidance in Shipping Lanes via Intelligent Sensor Data Fusion . This project aims to develop an online maritime traffic monitoring system for reliable collision/contact avoidance that exploits complementary data from high-resolution airborne sensors and surface vessel sensors. Our approach is based on optimal scheduling and fusion of the sensor data and possibly other sources of data to construct a comprehensive dynamic picture of maritime traffic, in real-time. Moreover, the proposed ....Collision Avoidance in Shipping Lanes via Intelligent Sensor Data Fusion . This project aims to develop an online maritime traffic monitoring system for reliable collision/contact avoidance that exploits complementary data from high-resolution airborne sensors and surface vessel sensors. Our approach is based on optimal scheduling and fusion of the sensor data and possibly other sources of data to construct a comprehensive dynamic picture of maritime traffic, in real-time. Moreover, the proposed methodology enables quantification of confidence in the predictions. This will provide ship owners, directly to their vessels and/or at the fleet management centres, information such as weather reports, reliable collision/no-collision warnings and avoidance strategies, on-the-fly. Read moreRead less