Studies in Statistical Signal Processing.
Abstract
The primary objective of our research is to develop efficient and numerically stable algorithms for nonstationary signal processing problems by understanding and exploiting special structures, both deterministic and stochastic, in the problems. We also strive to establish and broaden links with related disciplines, such as cascade filter synthesis, scattering theory, numerical linear algebra, and mathematical operator theory for the purpose of cross fertilization of ideas and techniques. These explorations have led to new results both in estimation theory and in these other fields, e.g., to new orthogonal cascade digital filter structures, new algorithms for triangular and QR factorization of structured matrices and new techniques for stability testing. For several years, the guiding principle in these studies has been the concept of (Toeplitz-oriented) displacement structure (Kailath, Kung and Morf, (1979)), which generalized and subsumed our earlier work on fast (Chandrasekhar) control and estimation algorithms for state-space models (Morf, Sidhu and Kailath, (1974)). Several authors have since picked up these ideas in a number of fields. A notable such work is a recent book by Heinig and K. Rost of East Germany, entitled 'Algebraic Methods for Toeplitz-Like Matrices and Operators'.
Document Details
- Document Type
- Technical Report
- Publication Date
- Aug 30, 1986
- Accession Number
- ADA177373
Entities
People
- Thomas Kailath
Organizations
- Stanford University