Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/28383
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Type: Conference paper
Title: Neural information transfer in a noisy environment
Author: McDonnell, M.
Pearce, C.
Abbott, D.
Citation: Electronics and structures for MEMS II : 17-19 December 2001, Adelaide, Australia / Neil W. Bergmann; Derek Abbott; Alex Hariz; Vijay K. Varadan (eds.), pp. 59-69
Publisher: THE SOCIETY OF PHOTO-OPTICAL INSTRUMENTATION ENGINEERS
Publisher Place: PO BOX 10 BELLINGHAM WASHINGTON USA
Issue Date: 2001
Series/Report no.: Proceedings of SPIE--the International Society for Optical Engineering ; 4591.
ISBN: 0819443212
ISSN: 0277-786X
1996-756X
Conference Name: Electronics and Structures for MEMS II (2nd : 2001 : Adelaide, Australia)
Editor: Bergmann, N.W.
Statement of
Responsibility: 
Mark D. McDonnell; Charles E. M.Pearce; Derek Abbott
Abstract: For an array of N summing comparators, each with the same internal noise, how should the set of thresholds, (theta) i, be arranged to maximize the information at the output, given the input signal, x, has an arbitrary probability density, P(x)? This problem is easy to solve when there is no internal noise. In this case, the transmitted information is equal to the entropy of the output signal, y. For N comparators there are N+1 possible output states and hence y can take on N+1 values. The transmitted information is maximized when all output states have the same probability of occupation, that is, 1/(N+1). In this paper we address some preliminary considerations relating to the maximization of the transmitted information I = H(y) - H(y|x) when there is finite internal noise.
Description: © SPIE--the International Society for Optical Engineering
DOI: 10.1117/12.449175
Published version: http://spie.org/x648.xml?product_id=449175
Appears in Collections:Aurora harvest 2
Electrical and Electronic Engineering publications

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