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 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, new realizations for multiple-input/multiple-output (MIMO) transfer functions, and new recursions for orthogonal polynomials on the unit circle and the real line as well as on other curves.

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Document Details

Document Type
Technical Report
Publication Date
Jun 30, 1990
Accession Number
ADA226825

Entities

People

  • Thomas Kailath

Organizations

  • Stanford University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Applied Mathematics
  • Complex Variables
  • Computations
  • Electrical Engineering
  • Engineering
  • Linear Algebra
  • Multiple Input Multiple Output
  • Network Science
  • Numerical Analysis
  • Parallel Computing
  • Power Series
  • Sequences
  • Signal Processing
  • Square Roots
  • Transfer Functions
  • Transmission Lines

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Linear Algebra
  • Systems Analysis and Design