Title :
Bilinear time series in non-Gaussian signal modeling
Author :
Valenzuela, H. ; Bose, N.
Author_Institution :
Pennsylvania State Univ., University Park, PA, USA
Abstract :
Non-Gaussian processes are taken to be the output of a bilinear system driven by a Gaussian white noise. The authors develop a 2D quarter-plane bilinear model as a nontrivial generalization of a 1D bilinear time series model. A maximum-likelihood-based parameter estimation method is then developed. Finally, the validity of the model is illustrated by simulation examples.<>
Keywords :
nonlinear systems; parameter estimation; signal processing; time series; 1D bilinear time series model; 2D quarter-plane bilinear model; Gaussian white noise; bilinear time series; maximum-likelihood-based parameter estimation; nonGaussian signal modeling; signal processing; Atmospheric modeling; Degradation; Filtering; High-resolution imaging; Linear systems; Nonlinear filters; Nonlinear systems; Optical imaging; Parameter estimation; White noise;
Conference_Titel :
Spectrum Estimation and Modeling, 1990., Fifth ASSP Workshop on
Conference_Location :
Rochester, NY, USA
DOI :
10.1109/SPECT.1990.205536
