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 :
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