IEEE/SP 13th workshop on Statistical Signal Processing July, 17-20, 2005 - Bordeaux - France

All papers by session

Quasi-separability and hierarchical quasi-separability in stochastic signal processing.
Plenary Lecture 6

Abstract

With the advent of array processing, the interest in structured systems has grown rapidly. One structure that is capable of handling very large systems efficiently goes under various names, quasi-separability, semi-separability, sysems of low Hankel rank or time-varying systems. We define what these systems are and how their main properties translate to efficient computations. Many real life systems, however, have a more involved structure that can be characterized as 'hierarchical quasi- (or semi-) separable'. We show ways to generalize the basic theory. We discuss several important applications in stochastic signal processing, namely optical flow analysis and signal detection and estimation with large spreading factors.