Implementation of iterative algorithms in a real time signal processing environment is described An this paper. The implementation considered here differs from the usual application of these algorithms in that the data flow is allowed to drive the iterations, providing effective real time performance. The particular signal processing application addressed is adaptive noise cancellation. We allow the data flow to continuously update the noise minimization problem, introducing perturbations in the problem. A perturbation analysis is given for the steepest descent algorithm. Numerical results are given for the steepest descent and conjugate gradient algorithms showing how the solution responds to perturbations in the data. An architecture is proposed for the steepest descent algorithm in a real time adaptive acousto-optic noise canceller.

Date Published: 25 November 1987
PDF: 9 pages
Proc. SPIE 0827, Real-Time Signal Processing X, (25 November 1987); doi: 10.1117/12.942056

Published in SPIE Proceedings Vol. 0827:
Real-Time Signal Processing X
J. P. Letellier, Editor(s)