Title :
Adaptive envelope-constrained filtering
Author :
Vo, Ba-Ngu ; Singh, Sumeetpal ; Tadic, Vladislav
Author_Institution :
Dept. of Electr. & Electron. Eng., Univ. of Melbourne, Vic., Australia
Abstract :
In the discrete-time envelope-constrained filtering problem, the gain of the filter is minimised subject to the constraint that the filter output to a prescribed input fits into a given envelope. A novel adaptive algorithm for solving this problem based on stochastic optimisation is presented. The algorithm is simple to implement on-line and convergence is demonstrated in numerical examples. Under mild regularity assumptions, convergence follows from standard stochastic approximation results.
Keywords :
adaptive filters; approximation theory; convergence of numerical methods; filtering theory; minimisation; stochastic processes; adaptive filtering; discrete-time filtering; envelope-constrained filtering; gain minimisation; numerical convergence; regularity assumptions; stochastic approximation; stochastic optimisation; Adaptive algorithm; Adaptive filters; Convergence; Filtering; Finite impulse response filter; IIR filters; Nonlinear filters; Pulse shaping methods; Quadratic programming; Stochastic processes;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on
Print_ISBN :
0-7803-7663-3
DOI :
10.1109/ICASSP.2003.1201689