Presentation 2001/3/9
Equivalent Property of Discrete-Time Cellular Neural Network
Yuichi TANJI,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) In this report, the goal is to consider synchronous/asynchronous DT-CNN computationally. Consequently, it is shown that DT-CNN is corresponding to nonlinear relaxation method for solving the equilibrium equation of the continuous-time CNN, where the networks are categorized into synchronous/asynchronous, by means of varieties for the nonlinear relaxation method. Further, it is shown that asynchronous DT-CNN is superior to asynchronous one from convergence property point of view and memoryless on the hardware implementation. In computer simulation, effectiveness of asynchronous DT-CNN is confirmed in the convergence property.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Discrete-Time Cellular Neural NetWork / Synchronous / Asynchronous / Nonlinear Relaxation Method
Paper # NLP2000-151
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Conference Information
Committee NLP
Conference Date 2001/3/9(1days)
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Paper Information
Registration To Nonlinear Problems (NLP)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Equivalent Property of Discrete-Time Cellular Neural Network
Sub Title (in English)
Keyword(1) Discrete-Time Cellular Neural NetWork
Keyword(2) Synchronous
Keyword(3) Asynchronous
Keyword(4) Nonlinear Relaxation Method
1st Author's Name Yuichi TANJI
1st Author's Affiliation Dept. of Reliability-based Information System Engineering, Kagawa University()
Date 2001/3/9
Paper # NLP2000-151
Volume (vol) vol.100
Number (no) 680
Page pp.pp.-
#Pages 5
Date of Issue