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 language||English (US)|
|Number of pages||5|
|Journal||ICASSP '78. IEEE International Conference on Acoustics, Speech, and Signal Processing|
|State||Published - 1978|
|Event||1978 IEEE International Conference on Acoustics, Speech & Signal Processing - Tulsa, United States|
Duration: Apr 10 1978 → Apr 12 1978
ASJC Scopus subject areas