Adaptive thresholds for neural networks with synaptic noise.

Adaptive thresholds for neural networks with synaptic noise. Research Abstract Details 

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Adaptive thresholds for neural networks with synaptic noise. Abstract Text:

D ,R Heylen,

The inclusion of a macroscopic adaptive threshold is studied for the retrieval dynamics of both layered feedforward and fully connected neural network models with synaptic noise. These two types of architectures require a different method to be solved numerically. In both cases it is shown that, if the threshold is chosen appropriately as a function of the cross-talk noise and of the activity of the stored patterns, adapting itself automatically in the course of the recall process, an autonomous functioning of the network is guaranteed. This self-control mechanism considerably improves the quality of retrieval, in particular the storage capacity, the basins of attraction and the mutual information content.

Adaptive thresholds for neural networks with synaptic noise. Publishing Authors By Initials

D ,R Heylen,

For similar nervous system: synapses research abstracts see: nervous system: synapses research

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Adaptive thresholds for neural networks with synaptic noise. Journal Published:

PUBLICATION TYPE: Research Support, Non-U.S. Gov

Journal: International journal of neural systems

VOLUME: 17

Page Numbers: 241-52

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ISSN: 0129-0657

DAY: 28

MONTH: Aug

YEAR: 2007

Adaptive thresholds for neural networks with synaptic noise. Information

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LANGUAGE: eng

NlmUniqueID: 9100527

Adaptive thresholds for neural networks with synaptic noise. Keywords Mesh Terms:

KEYWORDS: Synapses

MESH TERMS: physiology

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Grant and Affiliation Information for Adaptive thresholds for neural networks with synaptic noise.

AFFILIATION: Institute for Theoretical Physics, Katholieke Universiteit Leuven, Celestijnenlaan 200 D, B-3001, Leuven, Belgium. desire.bolle@fys.kuleuven.be

Country: Singapore

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MEDLINETA: Int J Neural Syst

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