Presentation 1995/11/17
Experimental Implementation and Estimation of DWT Processor Based on Hopfield Linear Programming Neural Network
Takeshi KAMIO, Hiroshi NINOMIYA, Hideki ASAI,
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Abstract(in English) Discrete Walsh transform (DWT) is one of the most important techniques as wen as the discrete Fourier transform (DFT) in the field of signal processing. We have proposed the theoretical design of the DWT processor based on Hopfield linear programming neural networks, and then we have also proved the rapid convergence and high accuracy of DWT processor both analytically and by simulation. In this report, we show the experimental design and the hardware implementation of the neuro-based DWT processor. Finally, it is confirmed both by the experiments and SPICE simulations that our processor is useful and practical.
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Keyword(in English) Neural Network / Discrete Walsh Transform / Steepest Descent Method / Orthogonal Matrix
Paper # NLP95-73
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Conference Information
Committee NLP
Conference Date 1995/11/17(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) Experimental Implementation and Estimation of DWT Processor Based on Hopfield Linear Programming Neural Network
Sub Title (in English)
Keyword(1) Neural Network
Keyword(2) Discrete Walsh Transform
Keyword(3) Steepest Descent Method
Keyword(4) Orthogonal Matrix
1st Author's Name Takeshi KAMIO
1st Author's Affiliation Department of System Eng., Faculty of Engineering, Shizuoka University()
2nd Author's Name Hiroshi NINOMIYA
2nd Author's Affiliation Department of System Eng., Faculty of Engineering, Shizuoka University
3rd Author's Name Hideki ASAI
3rd Author's Affiliation Department of System Eng., Faculty of Engineering, Shizuoka University
Date 1995/11/17
Paper # NLP95-73
Volume (vol) vol.95
Number (no) 368
Page pp.pp.-
#Pages 8
Date of Issue