Title :
New fast inverse QR least squares adaptive algorithms
Author :
Rontogiannis, A.A. ; Theodoridis, S.
Author_Institution :
Dept. of Inf., Athens Univ., Greece
Abstract :
The paper presents two new, closely related adaptive algorithms for LS system identification. The starting point for the derivation of the algorithms is the inverse Cholesky factor of the data correlation matrix, obtained via a QR decomposition (QRD). Both are of O(p) computational complexity with p being the order of the system. The first algorithm is a fixed order QRD scheme with enhanced parallelism. The second is a lattice type algorithm based on Givens rotations, with lower complexity compared to previously derived ones
Keywords :
adaptive filters; computational complexity; correlation methods; digital filters; identification; inverse problems; lattice filters; least squares approximations; matrix decomposition; parallel algorithms; Givens rotations; LS system identification; QR decomposition; computational complexity; data correlation matrix; fast inverse QR least squares adaptive algorithms; inverse Cholesky factor; lattice type algorithm; parallelism; quadratic residue; Adaptive algorithm; Finite impulse response filter; Informatics; Lattices; Least squares methods; Parallel processing; Resonance light scattering; Robustness; Signal processing algorithms; System identification;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1995. ICASSP-95., 1995 International Conference on
Conference_Location :
Detroit, MI
Print_ISBN :
0-7803-2431-5
DOI :
10.1109/ICASSP.1995.480506
