Comparisons of system identification methods in the presence of high noise levels and bandlimited inputs

L. R. Rabiner, R. E. Crochiere, J. B. Allen

Research output: Contribution to journalArticle

Abstract

The performance of three well known system identification methods based on an FIR (finite impulse response) model of the system is investigated. The methods are referred to as the least squares analysis (LSA) method, the least mean squares adaptation algorithm (LMS) and the short-time spectral analysis (SSA) procedure. The emphasis is on the performance of these algorithms in the presence of high noise levels and in situations where the input signal is bandlimited. Both white and nonwhite random noise signals as well as speech signals are used as test signals to measure the performance of the system identification techniques. Quantitative results in terms of an accuracy measure of system identification are presented and a simple analytical model is used to explain the measured results.

Original languageEnglish (US)
Pages (from-to)183-187
Number of pages5
JournalICASSP '78. IEEE International Conference on Acoustics, Speech, and Signal Processing
StatePublished - 1978
Event1978 IEEE International Conference on Acoustics, Speech & Signal Processing - Tulsa, United States
Duration: Apr 10 1978Apr 12 1978

ASJC Scopus subject areas

  • Engineering(all)

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