Optimum Quadratic Detection and Estimation Using Generalized Joint Signal Representations

Date
1996-12-01
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract

Time-frequency analysis has recently undergone significant advances in two main directions: statistically optimized methods that extend the scope of time-frequency-based techniques from merely exploratory data analysis to more quantitative application, and generalized joint signal representations that extend time-frequency-based methods to a richer class of nonstationary signals. This paper fuses the two advances by developing statistically optimal detection and estimation techniques based on generalized joint signal representations. By generalizing the statistical methods developed for time-frequency representations to arbitrary joint signal representations, this paper develops a unified theory applicable to a wide variety of problems in nonstationary statistical signal processing.

Description
Journal Paper
Advisor
Degree
Type
Journal article
Keywords
detection, estimation
Citation

A. M. Sayeed and D. L. Jones, "Optimum Quadratic Detection and Estimation Using Generalized Joint Signal Representations," IEEE Transactions on Signal Processing, 1996.

Has part(s)
Forms part of
Rights
Link to license
Citable link to this page