### Abstract

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 language | English |
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Title of host publication | Proceedings of the SICE Annual Conference |

Pages | 861-866 |

Number of pages | 6 |

Publication status | Published - 1994 |

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### ASJC Scopus subject areas

- Engineering(all)

### Cite this

*Proceedings of the SICE Annual Conference*(pp. 861-866)

**Separable estimation of discrete and continuous spectra based on genetic algorithm.** / Ohnishi, K.; Asida, H.; Sano, A.

Research output: Chapter in Book/Report/Conference proceeding › Chapter

*Proceedings of the SICE Annual Conference.*pp. 861-866.

}

TY - CHAP

T1 - Separable estimation of discrete and continuous spectra based on genetic algorithm

AU - Ohnishi, K.

AU - Asida, H.

AU - Sano, A.

PY - 1994

Y1 - 1994

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=0028746732&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0028746732&partnerID=8YFLogxK

M3 - Chapter

AN - SCOPUS:0028746732

SP - 861

EP - 866

BT - Proceedings of the SICE Annual Conference

ER -