Presentation 1995/9/29
DESIGN METHODOLOGY OF NEURAL NETWORKS AND THEIR APPLICATIONS TO ASSOCIATIVE MEMORY AND SIGNAL PROCESSING
Kenji NAKAYAMA,
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Abstract(in English) This tutorial paper surveys recent research and development on neural networks. Especially, stress is placed on comparison between neural networks and signal processing technology. Neural networks have similarities in structures and learning algorithms. However, neural networks have the following features, nonparametric scheme, dynamic systems, self-organization, robustness due to parallel and distributed structure. So, we can expect more efficient and flexible signal processing. Usefulness of neural networks is dependent of relations between neural networks and unknown systems of interest in structures and nonlinearity The applications In signal processing and digital transmission taking the features into account are also surveyed.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) neural networks / nonlinearity / signal processing / dynamics / associative memory / system identification
Paper # NLP95-46
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Conference Information
Committee NLP
Conference Date 1995/9/29(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) DESIGN METHODOLOGY OF NEURAL NETWORKS AND THEIR APPLICATIONS TO ASSOCIATIVE MEMORY AND SIGNAL PROCESSING
Sub Title (in English)
Keyword(1) neural networks
Keyword(2) nonlinearity
Keyword(3) signal processing
Keyword(4) dynamics
Keyword(5) associative memory
Keyword(6) system identification
1st Author's Name Kenji NAKAYAMA
1st Author's Affiliation Dept. of Electrical and Computer Engineering, Faculty of Eng., Kanazawa Univ.()
Date 1995/9/29
Paper # NLP95-46
Volume (vol) vol.95
Number (no) 280
Page pp.pp.-
#Pages 8
Date of Issue