Presentation 2003/10/16
The Path-Integral Analysis of Associative Memory Model Storing Infinite Number of Limit Cycles
Kazushi MIMURA, Masaki KAWAMURA, Masato OKADA,
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Abstract(in English) We rigorously analysed an associative memory model storing an infinite number or limit cycles with l finite steps by using the path-integral method. We derived the stationary versions of the order parameter equations given by the path-integral analysis. Although the signal-to-noise analysis must assume that crosstalk noise of an input to spins obeys a Gaussian distribution, the stationary versions of the order parameter equations are equivalent to those of the signal-to-noise analysis. This means that the result of signal-to-noise analysis is an exact solution. We also obtained that the dependence of storage capacity (α_c) on the number of patterns per one limit cycle (l). At l = 1, storage capacity is α_c = 0.138 as well as Hopfield model. A storage capacity monotonously increases with the increase in the number of steps, and converges α_c = 0.269 at l ≃ 10. The original propoerties of the finite-step sequence processing model appear as long as the number of steps of a limit cycle has order l = O1).
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Keyword(in English) Associative Memory Model / limit Cycles / Path-Integral Method / Stationary State / Exact Solution
Paper # PRMU2003-116,NC2003-47
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Committee NC
Conference Date 2003/10/16(1days)
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Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) The Path-Integral Analysis of Associative Memory Model Storing Infinite Number of Limit Cycles
Sub Title (in English)
Keyword(1) Associative Memory Model
Keyword(2) limit Cycles
Keyword(3) Path-Integral Method
Keyword(4) Stationary State
Keyword(5) Exact Solution
1st Author's Name Kazushi MIMURA
1st Author's Affiliation Kobe City College of Technology()
2nd Author's Name Masaki KAWAMURA
2nd Author's Affiliation Faculty of Science, Yamaguchi University
3rd Author's Name Masato OKADA
3rd Author's Affiliation Laboratory for Mathematical Neuroscience, RIKEN Brain Science Institute, "Intelligent Cooperation and Control", PRESTO, JST
Date 2003/10/16
Paper # PRMU2003-116,NC2003-47
Volume (vol) vol.103
Number (no) 391
Page pp.pp.-
#Pages 6
Date of Issue