Title :
Adaptive IIR filtering using input/output orthogonalization
Author :
Beex, A.A. ; Sankaran, Sundar G.
Author_Institution :
Syst. Group-DSP Res. Lab., Virginia Polytech. Inst. & State Univ., Blacksburg, VA, USA
Abstract :
An adaptive IIR filter structure is proposed based on orthogonal representations of the input and the (noisy) output. The orthogonalization of the input comes from the backward prediction errors in the lattice predictor. The input orthogonalization is then extended using the output, so that a single orthogonal decomposition results. Consequently the Hessian approximation becomes diagonal. The adaptive IIR filter weights converge rapidly compared to their direct form counterparts.
Keywords :
Hessian matrices; IIR filters; adaptive filters; adaptive signal processing; convergence of numerical methods; digital filters; filtering theory; least squares approximations; noise; prediction theory; adaptive IIR filter structure; adaptive IIR filtering; backward prediction errors; diagonal Hessian approximation; direct form weights; filter weights convergence; input/output orthogonalization; lattice predictor; least squares lattice predictor; noisy output; orthogonal decomposition; orthogonal representations; Adaptive filters; Convergence; Cost function; Equations; Filtering algorithms; Finite impulse response filter; IIR filters; Noise measurement; Poles and zeros; Transfer functions;
Conference_Titel :
Signals, Systems & Computers, 1998. Conference Record of the Thirty-Second Asilomar Conference on
Conference_Location :
Pacific Grove, CA, USA
Print_ISBN :
0-7803-5148-7
DOI :
10.1109/ACSSC.1998.750914
