Simultaneous optimization method of regularization and singular value decomposition in least squares parameter identification

A. Sano, T. Furuya, H. Tsuji, H. Ohmori

Research output: Contribution to journalConference articlepeer-review

4 Citations (Scopus)

Abstract

In order to attain stabilized convergence, the authors propose a generalized regularization scheme using multiple regularization parameters and an a priori estimate, and they obtain analytically the parameter values that minimize the mean-square error (MSE) or the estimated MSE using only accessible data signals. They show that method can give simultaneously the optimal regularization parameters and the optimal truncation of smaller eigenvalues in the singular value (or eigenvalue) decomposition (SVD or EVD). The proposed schemes for the optimized regularization and SVD are exemplified in impulse response identification using low-pass input and optimized extrapolation of the bandlimited signal.

Original languageEnglish
Pages (from-to)2290-2293
Number of pages4
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume4
Publication statusPublished - 1989 Dec 1
Event1989 International Conference on Acoustics, Speech, and Signal Processing - Glasgow, Scotland
Duration: 1989 May 231989 May 26

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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