Title :
An RKHS approach to robust L2 estimation and signal detection
Author :
Barton, Richard J. ; Poor, H. Vincent
Author_Institution :
ORINCON Corp., San Diego, CA, USA
fDate :
5/1/1990 12:00:00 AM
Abstract :
The application of RKHS (reproducing kernel Hilbert space) theory to the problems of robust signal detection and estimation is investigated. It is shown that this approach provides a general and unified framework in which to analyze the problems of L2 estimation, matched filtering, and quadratic detection in the presence of uncertainties regarding the second-order structure of the random processes involved
Keywords :
filtering and prediction theory; matched filters; parameter estimation; signal detection; RKHS approach; matched filtering; quadratic detection; random processes; reproducing kernel Hilbert space; robust L2 estimation; signal detection; Filtering; Hilbert space; Kernel; Matched filters; Minimax techniques; Noise robustness; Nonlinear filters; Random processes; Signal detection; Uncertainty;
Journal_Title :
Information Theory, IEEE Transactions on
