System Modeling and Statistical Data Processing.
Abstract
This report is a summary of research accomplishments by the two authors and their associates resulting from their investigations into several aspects of systems modeling and statistical data processing. Brief summaries of the numerous technical papers and presentations are presented, covering the major areas of (1) the innovations approach to linear least-squares estimation, (2) other applications of the innovations approach, (3) martingale theory applied to non-Gaussian and nonlinear signal detection and estimation, (4) applications of reproducing kernel Hilbert space theory, (5) fast algorithms for multivariable system modeling, estimation and control, (6) studies in multivariable systems theory, (7) nearest neighbor pattern recognition, (8) learning with finite memory, (9) broadcast channels, and (10) Kolmogorov complexity and pattern recognition. (Modified author abstract)
Document Details
- Document Type
- Technical Report
- Publication Date
- Aug 01, 1974
- Accession Number
- AD0785290
Entities
People
- Thomas Kailath
- Thomas M. Cover
Organizations
- Stanford University