Mark McDonnell's Projects Page

My research interests fall into three broad categories:

• Information Theory: In particular, lossy compression and distributed compression.

• Computational Neuroscience: This is defined, according to Wikipedia, as: "...an interdisciplinary field which draws on neuroscience, computer science, and applied mathematics. It most often uses mathematical and computational techniques such as computer simulations and mathematical models to understand the function of the nervous system."

• Biologically Inspired Signal Processing and Electronics

Sensory Neural Coding

• Neural Information Theory: Combining computational neuroscience with information theory to model and analyse how biology encodes and transmits sensory stimuli, and overcomes random noise.

Distributed Compression

• Information Theoretic Approaches: Lossy compression and transmission of observed data in noisy distributed sensor networks, e.g. the CEO problem.

Stochastic quantization

• Suprathreshold Stochastic Resonance

• Quantization and Lossy Compression in the presence of random noise.

Applications

• Stochastic ADCs: Application of stochastic quantization and distributed compression theory to new analog-to-digital converter designs, and digital signal processing.

• Bio-inspired Engineering: Application of new insights on how neurons encode and transmit information to engineered electronic systems.

Collaborators

• Nigel Stocks, The University of Warwick, UK
• Rob Morse, Aston University, UK
• Pierre-Olivier Amblard, Laboratoire des Images et des Signaux, France
• Anthony Burkitt, The Bionic Ear Institute, Auustralia
• Simon Brookes, Flinders University Centre for Neuroscience, Australia
• Ferran Martorell, Antonio Rubio, The Technical University of Catalonia, Spain

Copyright © The University of Adelaide 2006 Last Modified Webmaster
Copyright | Privacy | Disclaimer