Title :
Hyperspherical parametrization for unit-norm based adaptive IIR filtering
Author :
Sankaran, S.G. ; Beex, A. A. Louis
Author_Institution :
Bradley Dept. of Electr. Eng., Virginia Polytech. Inst. & State Univ., Blacksburg, VA, USA
Abstract :
The bias problem associated with equation error based adaptive infinite impulse response (IIR) filtering can be surmounted by imposing a unit-norm constraint on the autoregressive (AR) coefficients. We propose a hyperspherical parameterization to convert the unit-norm-constrained optimization into an unconstrained optimization. We show that the hyperspherical parameterization does not introduce any additional minima to the equation error surface.
Keywords :
IIR filters; adaptive filters; autoregressive processes; filtering theory; minimisation; optimisation; AR coefficients; adaptive IIR filtering; adaptive infinite impulse response filtering; autoregressive AR coefficients; equation error minimisation; equation error surface; hyperspherical parametrization; unconstrained optimization; unit-norm constraint; unit-norm-constrained optimization; Adaptive filters; Computational complexity; Constraint optimization; Digital signal processing; Equations; Filtering; Finite impulse response filter; IIR filters; Lagrangian functions; Poles and zeros;
Journal_Title :
Signal Processing Letters, IEEE
