Presentation 1997/6/27
Simplification of Stochastic Fastest Convergence NLMS Algorithm
Masahiro FUKUMOTO, Hajime KUBOTA, Shigeo TSUJII,
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Abstract(in English) The normalized LMS (NLMS) algorithm behaves unstably when all elements of an input state vector is very small. This property is caused by the division in the procedure of the NLMS algorithm. One of the countermeasures against this problem has been taken that coefficients of an adaptive filter are not updated when a norm of an input state vector is smaller than a threshold. The least upper bound of the estimation error with interrupt coefficients update and the stochastic fastest convergence step gain have been shown. In this paper, we show the simplifycation of the above method.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) NLMS algorithm / interruption of coefficients update / guarantee value / stochastic fastest convergence / step gain / S/N
Paper # CAS97-19
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Conference Information
Committee DSP
Conference Date 1997/6/27(1days)
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Registration To Digital Signal Processing (DSP)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Simplification of Stochastic Fastest Convergence NLMS Algorithm
Sub Title (in English)
Keyword(1) NLMS algorithm
Keyword(2) interruption of coefficients update
Keyword(3) guarantee value
Keyword(4) stochastic fastest convergence
Keyword(5) step gain
Keyword(6) S/N
1st Author's Name Masahiro FUKUMOTO
1st Author's Affiliation Department of Information Systems Engineering, Kochi University of Technology()
2nd Author's Name Hajime KUBOTA
2nd Author's Affiliation Department of Electrical Engineering, Chiba Institute of Technology
3rd Author's Name Shigeo TSUJII
3rd Author's Affiliation Department of Information and System Engineering, Faculty of Science and Engneering, Chuo University
Date 1997/6/27
Paper # CAS97-19
Volume (vol) vol.97
Number (no) 141
Page pp.pp.-
#Pages 6
Date of Issue