Title :
Multichannel adaptive least squares-relating the `Kalman´ recursive least squares (RLS) and least squares lattice (LSL) adaptive algorithms
Author_Institution :
Los Alamos Nat. Lab., NM, USA
Abstract :
A multichannel adaptive lattice algorithm is derived that provides a least-squares estimate of a primary signal in terms of the last p samples of m reference signals. The recursions developed are optimized for multichannel use and provide an algorithm with computational complexity O(pm2). In the single reference channel case (m=1), the algorithm simplifies to the O(p) least-squares lattice (LSL) algorithm. In the single filter tap case (p=1), the algorithm simplifies to the O(m 2) `Kalman´ recursive least-squares (RLS) algorithm. Hence, the general multichannel least-squares lattice (MLSL) presented provides an explicit relationship between, and common derivation of, both the LSL and RLS algorithms
Keywords :
Kalman filters; filtering and prediction theory; least squares approximations; Kalman recursive least squares; computational complexity; least squares lattice algorithm; multichannel adaptive lattice algorithm; multichannel least-squares lattice; primary signal; reference signals; Adaptive algorithm; Finite impulse response filter; Kalman filters; Laboratories; Lattices; Least squares approximation; Least squares methods; Postal services; Resonance light scattering; Robustness;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1988. ICASSP-88., 1988 International Conference on
Conference_Location :
New York, NY
DOI :
10.1109/ICASSP.1988.197004
