Presentation	2008-02-01 A Generalised Entropy based Associative Memory Masahiro NAKAGAWA,
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Abstract(in English)	In this paper, a generalised entropy based associative memory model will be proposed and applied to memory retrievals with analogue embedded vectors instead of the binary ones in order to compare with the conventional autoassociative model with a quadratic Lyapunov functionals. In the present approach, the updating dynamics will be constructed on the basis of the entropy minimization strategy which may be reduced asymptotically to the autocorrelation dynamics as a special case. From numerical results, it will be found that the presently proposed novel approach realizes a relatively large memory capacity even for the analogue memory retrievals in comparison with the autocorrelation model based on dynamics such as associatron according to the higher-order correlation involved in the proposed dynamics.
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Keyword(in English)	Entropy / Associative Memory / Memory Capacity
Paper #	NLP2007-146
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Conference Information
Committee	NLP
Conference Date	2008/1/25(1days)
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Paper Information
Registration To	Nonlinear Problems (NLP)
Language	ENG
Title (in Japanese)	(See Japanese page)
Sub Title (in Japanese)	(See Japanese page)
Title (in English)	A Generalised Entropy based Associative Memory
Sub Title (in English)
Keyword(1)	Entropy
Keyword(2)	Associative Memory
Keyword(3)	Memory Capacity
1st Author's Name	Masahiro NAKAGAWA
1st Author's Affiliation	Nagaoka University of Technology()
Date	2008-02-01
Paper #	NLP2007-146
Volume (vol)	vol.107
Number (no)	478
Page	pp.pp.-
#Pages	6
Date of Issue