Stochastic Resonance
From Suprathreshold Stochastic Resonance to Stochastic Signal Quantization

This book addresses aspects of stochastic quantization for researchers in fields from computational neuroscience through to electronic engineering.

Mark D. McDonnell (Author), Nigel G. Stocks (Author), Charles E. M. Pearce (Author), Derek Abbott (Author)

9780521882620, Cambridge University Press

Hardback, published 2 October 2008

448 pages
25.3 x 17.9 x 2.5 cm, 1.02 kg

Review of the hardback: 'A major strength of this book is its capture of the expertise of four leading exponents of stochastic resonance research. Four heads here certainly provide an optimal performance. Take home messages from all the chapters are provided in clear 'in a nutshell' summaries. … the authors have rendered a major service to a multi-disciplinary research community which can benefit from the clarity of exposition offered in this book. It is to be hoped that that community will repay its debt to these authors by taking forward wherever possible applications of stochastic resonance.' Contemporary Physics

Stochastic resonance has been observed in many forms of systems, and has been hotly debated by scientists for over 30 years. Applications incorporating aspects of stochastic resonance may yet prove revolutionary in fields such as distributed sensor networks, nano-electronics, and biomedical prosthetics. Ideal for researchers in fields ranging from computational neuroscience through to electronic engineering, this book addresses in detail various theoretical aspects of stochastic quantization, in the context of the suprathreshold stochastic resonance effect. Initial chapters review stochastic resonance and outline some of the controversies and debates that have surrounded it. The book then discusses suprathreshold stochastic resonance, and its extension to more general models of stochastic signal quantization. Finally, it considers various constraints and tradeoffs in the performance of stochastic quantizers, before culminating with a chapter in the application of suprathreshold stochastic resonance to the design of cochlear implants.

Preface
1. Introduction and motivation
2. Stochastic resonance: its definitions, history and debates
3. Stochastic quantization
4. Suprathreshold stochastic resonance: encoding
5. Suprathreshold stochastic resonance: large N encoding
6. Suprathreshold stochastic resonance: decoding
7. Suprathreshold stochastic resonance: large N decoding
8. Optimal stochastic quantization
9. SSR, neural coding, and performance tradeoffs
10. Stochastic resonance in the auditory system
11. The future of stochastic resonance and suprathreshold stochastic resonance
Appendices
References
Index.

Subject Areas: Electronics & communications engineering [TJ], Electrical engineering [THR], Nanotechnology [TBN], Neurosciences [PSAN], Nonlinear science [PBWR], Mathematics [PB], Prosthetics [MQWP], Biomedical engineering [MQW]