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 cascades filter synthesis, scattering theory, numerical linear algebra, and mathematical operatory 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 algorithms for triangular and QR factorization of structured matrices, new techniques for root location and stability testing, and new recursions for orthogonal polynomials on the unit circle and the real line as well as on other curves.
Document Details
- Document Type
- Technical Report
- Publication Date
- Aug 01, 1989
- Accession Number
- ADA214490
Entities
People
- Thomas Kailath
Organizations
- Stanford University