Title :
Adaptive bilinear predictors
Author :
Lee, Junghsi ; Mathews, V. John
Author_Institution :
Comput. & Commun. Res. Lab., Ind. Technol. Res. Inst., Hsinchu, Taiwan
Abstract :
This paper considers an extended recursive least squares (RLS) adaptive bilinear predictor. It is shown that the extended RLS adaptive bilinear predictor is guaranteed to be stable in the sense that the time average of the squared a-posteriori prediction error signal is bounded whenever the input signal is bounded in the same sense. It also shows that the a-priori prediction error itself is bounded whenever the desired signal is bounded. This paper also contains simulation results to demonstrate the usefulness of the extended RLS adaptive bilinear predictor
Keywords :
adaptive signal processing; bilinear systems; least squares approximations; prediction theory; recursive estimation; stability; time series; a-priori prediction error; bilinear time series; extended RLS adaptive bilinear predictor; input signal; prediction error signal; recursive least squares; simulation results; squared a-posteriori prediction error; stability results; time average; Biological system modeling; Control system synthesis; Difference equations; Ear; Economic forecasting; Filtering; Nonlinear systems; Polynomials; Resonance light scattering; Stability;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1994. ICASSP-94., 1994 IEEE International Conference on
Conference_Location :
Adelaide, SA
Print_ISBN :
0-7803-1775-0
DOI :
10.1109/ICASSP.1994.389983
