Presentation 1995/5/19
A constitution method of an optimum FIR filter by use of Sandglass Neural Network
Hiroki Yoshimura, Kazuhiro Sugata, Naoki Isu, Tadaaki Shimizu,
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Abstract(in English) We proposed the way of constituting an optimum FIR filter by using the sand glass neural network. We showed through the experiment by use of the signal generated auto-regressive model that our FIR filter can be constituted conveniently to correspond to the frequency characteristics of time series signals inputted at the learning stage. The frequency pass band of our FIR filter can be adjusted by varying the number of units in the input layer. So we can set up the frequency pass band very easily according to the purpose of signal processing.
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Keyword(in English) neural network / FIR filter / auto-regressive model / signal processing / optimization
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Conference Information
Committee NLP
Conference Date 1995/5/19(1days)
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Registration To Nonlinear Problems (NLP)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A constitution method of an optimum FIR filter by use of Sandglass Neural Network
Sub Title (in English)
Keyword(1) neural network
Keyword(2) FIR filter
Keyword(3) auto-regressive model
Keyword(4) signal processing
Keyword(5) optimization
1st Author's Name Hiroki Yoshimura
1st Author's Affiliation Department of Information and Knowledge Engineering, Tottori University()
2nd Author's Name Kazuhiro Sugata
2nd Author's Affiliation Department of Information and Knowledge Engineering, Tottori University
3rd Author's Name Naoki Isu
3rd Author's Affiliation Department of Information and Knowledge Engineering, Tottori University
4th Author's Name Tadaaki Shimizu
4th Author's Affiliation Department of Information and Knowledge Engineering, Tottori University
Date 1995/5/19
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Volume (vol) vol.95
Number (no) 47
Page pp.pp.-
#Pages 8
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