Presentation 1998/12/11
Introduction of Orthogonal Transform into Multi- layered Neural Filter
Isao Nakanishi, Yoshio Itoh, Yutaka Fukui,
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Abstract(in English) A neural filter adopts the neural networks as a non-linear adaptive system. It is effective for the system identification of the non-linear system and the noise reduction in the non-linear signal. However, it has been a problem for the neural filter to require large number of iterations for learning (convergence). In this paper, to accelerate the convergence speed of the neural filter essentially, we propose to introduce the orthogonal transform into the neural filter. In the Transform Domain Neural Filter (TDNF) (I) the input signal is transformed by the orthogonal trandform, then led to the input layer. The TDNF (II) introduces the orthogonal transform in all connection of layers. Through the computer simulation in the non-linear system identification, it is confirmed that the introduction of the orthogonal transform is effective for speed-up of convergence in the neural filter.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) neural filter / neural network / orthogonal transform / speed-up of convergence
Paper # DSP98-143
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Conference Information
Committee DSP
Conference Date 1998/12/11(1days)
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Paper Information
Registration To Digital Signal Processing (DSP)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Introduction of Orthogonal Transform into Multi- layered Neural Filter
Sub Title (in English)
Keyword(1) neural filter
Keyword(2) neural network
Keyword(3) orthogonal transform
Keyword(4) speed-up of convergence
1st Author's Name Isao Nakanishi
1st Author's Affiliation Faculty of Education, Tottori University()
2nd Author's Name Yoshio Itoh
2nd Author's Affiliation Faculty of Engineering, Tottori University
3rd Author's Name Yutaka Fukui
3rd Author's Affiliation Faculty of Engineering, Tottori University
Date 1998/12/11
Paper # DSP98-143
Volume (vol) vol.98
Number (no) 451
Page pp.pp.-
#Pages 8
Date of Issue