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11 - The future of stochastic resonance and suprathreshold stochastic resonance

Published online by Cambridge University Press:  23 October 2009

Mark D. McDonnell
Affiliation:
Institute for Telecommunications Research, University of South Australia and University of Adelaide
Nigel G. Stocks
Affiliation:
University of Warwick
Charles E. M. Pearce
Affiliation:
University of Adelaide
Derek Abbott
Affiliation:
University of Adelaide
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Summary

To conclude this book, we summarize our main results and conclusions, before briefly speculating on the most promising areas for future research.

Putting it all together

Stochastic resonance

Chapter 2 presents a historical review and elucidation of the major epochs in the history of stochastic resonance (SR) research, and discussion of the evolution of the term ‘stochastic resonance’. A list of the main controversies and debates associated with the field is given.

Chapter 2 also demonstrates qualitatively that SR can actually occur in a single threshold device, where the threshold is set to the signal mean. Although SR cannot occur in the conventional signal-to-noise ratio (SNR) measure in this situation, if ensemble averaging is allowed, then the presence of an optimal noise level can decrease distortion.

Furthermore, Chapter 2 contains a discussion and critique of the use of SNR measures to quantify SR, the debate about SNR gains due to SR, and the relationship between SNRs and information theory.

Suprathreshold stochastic resonance

Chapter 4 provides an up-to-date literature review of previous work on suprathreshold stochastic resonance (SSR). It also gives numerical results, showing SSR occurring for a number of matched and mixed signal and noise distributions not previously considered. A generic change of variable in the equations used to determine the mutual information through the SSR model is introduced. This change of variable results in a probability density function (PDF) that describes the average transfer function of the SSR model.

Type
Chapter
Information
Stochastic Resonance
From Suprathreshold Stochastic Resonance to Stochastic Signal Quantization
, pp. 358 - 361
Publisher: Cambridge University Press
Print publication year: 2008

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