Separable estimation of discrete and continuous spectra based on genetic algorithm

K. Ohnishi, H. Asida, A. Sano

Research output: Contribution to journalArticlepeer-review


This paper is concerned with a method for separately estimating line and continuous spectra of signals which are composed of multiple sinusoids and an autoregressive (AR) noise. The whitening filter approach is proposed in which the frequency estimates are obtained by applying the Toeplitz approximation method to the output of the whitening filter. The filter coefficients which correspond to the AR parameters are iteratively calculated so as to minimize the squared prediction error criterion, however, the solution is a local minimum. By employing the genetic algorithm in the choice of initial values of the iterative AR parameter estimation, we can attain a globally optimal solution. The decision rule for deciding the number of sinusoids and the order of the AR model is also investigated. The validity of the proposed algorithm is examined in numerical simulations including a benchmark example.

Original languageEnglish
Pages (from-to)861-866
Number of pages6
JournalProceedings of the SICE Annual Conference
Publication statusPublished - 1994 Dec 1

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering


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