Title :
Adaptive IIR filtering using QR matrix decomposition
Author :
Harteneck, Moritz ; Stewart, Robert W.
Author_Institution :
Signal Process. Div., Strathclyde Univ., Glasgow, UK
fDate :
9/1/1998 12:00:00 AM
Abstract :
In this correspondence, an approach to adaptive IIR filtering based on a pseudo-linear regression and applying an iterative QR matrix decomposition is developed. In simulations, the algorithm has shown a high stability and excellent convergence properties. The derivation of the IIR-QR adaptive filter is straightforward, and the computational complexity of the algorithm is comparable with the FIR-QR adaptive algorithm of the same order and less than gradient-based adaptive IIR filters such as the simplified-gradient recursive prediction error (RPE) algorithm. Fast versions of O(N) computational complexity are readily available
Keywords :
IIR filters; adaptive filters; adaptive signal processing; computational complexity; filtering theory; iterative methods; matrix decomposition; numerical stability; IIR-QR adaptive filter; adaptive IIR filtering; computational complexity; convergence properties; digital signal processing; high stability; iterative QR matrix decomposition; pseudo-linear regression; Adaptive filters; Computational complexity; Computational modeling; Convergence; Filtering; IIR filters; Iterative algorithms; Iterative methods; Matrix decomposition; Stability;
Journal_Title :
Signal Processing, IEEE Transactions on