Title :
Fast sequential least-squares processing
Author :
Milios, Evangelos
Author_Institution :
Massachusetts Institute of Technology, Cambridge, MA
Abstract :
A fast algorithm with reduced memory requirements for updating in time the covariance autoregressive model of a time series with constant memory is proposed. The "algorithm is derived using elementary linear algebra concepts and manipulations and is based on the special structure of the covariance matrix characterizing the underlying linear equations. The algorithm is extended to updating the all-zero (or all-pole) least-squares model of a system, computed from its input and output signals.
Keywords :
Adaptive arrays; Approximation algorithms; Approximation error; Covariance matrix; Differential equations; Least squares approximation; Linear algebra; Linear approximation; Noise cancellation; Vectors;
Conference_Titel :
Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP '84.
DOI :
10.1109/ICASSP.1984.1172521
