This paper studies the parallel processing algorithms of digital signal linear prediction, especially in speech signals and image signals. An autoregressive digital signal vector series with stable covariance can be obtained by grouping adjacent samples of signal source series and a strategy for vector predictive coding with highly parallel processing ability can be achieved by applying the principle of orthogonal projection in Hilbert space. Then an adaptive parallel processing algorithms for digital signal linear prediction can be given. Compared with traditional lattice methods, the algorithms have an obvious progress in the computation complexity and storage. Finally its performance is tested by computer simulation.

Date Published: 2 September 2003
PDF: 4 pages
Proc. SPIE 5253, Fifth International Symposium on Instrumentation and Control Technology, (2 September 2003); doi: 10.1117/12.521478

Published in SPIE Proceedings Vol. 5253:
Fifth International Symposium on Instrumentation and Control Technology
Guangjun Zhang; Huijie Zhao; Zhongyu Wang, Editor(s)