DocumentCode
925405
Title
2-D recursive bilinear model for nonlinear signal representation
Author
Valenzuela, Hector M. ; Jabbi, Amandeep S.
Author_Institution
Dept. of Electr. & Comput. Eng., Pennsylvania State Univ., University Park, PA, USA
Volume
40
Issue
4
fYear
1993
fDate
4/1/1993 12:00:00 AM
Firstpage
241
Lastpage
250
Abstract
Develops 2-D recursive bilinear models for quarter-plane and weakly causal random fields. These models are obtained as a nontrivial generalization to two dimensions of the 1-D bilinear time series and satisfy a 2-D bilinear recursion where the coefficients lie on a causality cone. The extended support of the coefficients results in greater model flexibility. An efficient maximum-likelihood estimation method for order determination and parameter estimation has been obtained. Computer simulations are included to illustrate this model and the performance of the parameter estimation technique
Keywords
parameter estimation; signal detection; 2D models; bilinear recursion; bilinear time series; causality cone; maximum-likelihood estimation method; model flexibility; nonlinear signal representation; nontrivial generalization; order determination; parameter estimation; quarter-plane fields; recursive bilinear model; weakly causal random fields; Degradation; Digital filters; Digital signal processing; Linear systems; Nonlinear filters; Nonlinear systems; Optical imaging; Parameter estimation; Signal representations; Two dimensional displays;
fLanguage
English
Journal_Title
Circuits and Systems II: Analog and Digital Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1057-7130
Type
jour
DOI
10.1109/82.224315
Filename
224315
Link To Document