Model order selection method for multiple structured time sequence signals

Kiyohito Tokuda*, Yumi Takizawa, Satoru Shimizu, Atsushi Fukasawa

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

2 Citations (Scopus)


A novel method of model order selection and separation of spectral structures is proposed for practical signals which are composed of multiple structured spectra. The input time sequence signal is considered to have multiple spectral structure, i.e., a main spectral structure and a residual spectral structure. The main structure is determined by the signal dominant power spectral component of the input signal and the residual structure is defined by the residual power spectral component after the dominant power spectral component is removed from the whole spectral structure. The method first estimates the dominant spectrum of the main structure using the AR (autoregressive) model with order p[AR (p)] and then estimates the spectrum of the residual structure using the AR model with order q[AR (q)]. By computer simulation, the method is proved to give a good solution to the problem of reliable spectral estimation.

Original languageEnglish
Pages (from-to)2431-2434
Number of pages4
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Publication statusPublished - 1990
Externally publishedYes
Event1990 International Conference on Acoustics, Speech, and Signal Processing: Speech Processing 2, VLSI, Audio and Electroacoustics Part 2 (of 5) - Albuquerque, New Mexico, USA
Duration: 1990 Apr 31990 Apr 6

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering


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