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|Title:||Optimal information transmission in nonlinear arrays through suprathreshold stochastic resonance|
|Citation:||Physics Letters A, 2006; 352(3):183-189|
|Publisher:||Elsevier Science BV|
|Mark D. McDonnell, Nigel G. Stocks, Charles E.M. Pearce and Derek Abbott|
|Abstract:||We examine the optimal threshold distribution in populations of noisy threshold devices. When the noise on each threshold is independent, and sufficiently large, the optimal thresholds are realized by the suprathreshold stochastic resonance effect, in which case all threshold devices are identical. This result has relevance for neural population coding, as such noisy threshold devices model the key dynamics of nerve fibres. It is also relevant to quantization and lossy source coding theory, since the model provides a form of stochastic signal quantization. Furthermore, it is shown that a bifurcation pattern appears in the optimal threshold distribution as the noise intensity increases. Fisher information is used to demonstrate that the optimal threshold distribution remains in the suprathreshold stochastic resonance configuration as the population size approaches infinity.|
|Keywords:||Information theory; neural coding; suprathreshold stochastic resonance; quantization; optimal quantization; population coding; bifurcations; point density function|
|Appears in Collections:||Electrical and Electronic Engineering publications|
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