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https://hdl.handle.net/2440/28484
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Type: | Conference paper |
Title: | Optimal quantization in neural coding |
Author: | McDonnell, M. Abbott, D. |
Citation: | Proceedings of the 2004 IEEE International Symposium on Information Theory:pp.494 |
Publisher: | IEEE |
Publisher Place: | New Jersey, USA |
Issue Date: | 2004 |
ISBN: | 0780382803 |
Conference Name: | ISIT 2004 (2004 : Chicago, USA) |
Editor: | Kschischang, F. Tse, D. |
Statement of Responsibility: | McDonnell, M.; Abbott, D. |
Abstract: | In this paper the optimality of the encoding by relaxing the constraint of identical threshold values for each neuron and determining the optimal encoding for a range of SNR's is presented. The population of neurons can be considered a semicontinuous information channel. Using Fisher information that the value of SNR at which bifurcation occurs asymptotically approaches a fixed value of SNR. This result indicates that in the presence of low SNR's, populations of neurons may be able to effectively encode information in a manner similar to a flash analog to digital converter, despite possessing identical thresholds. |
Description: | Copyright © 2004 IEEE |
DOI: | 10.1109/ISIT.2004.1365533 |
Published version: | http://dx.doi.org/10.1109/isit.2004.1365533 |
Appears in Collections: | Aurora harvest 6 Electrical and Electronic Engineering publications |
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