On multidimensional system identification

Author

Zhao, Ping-ya ; He, Zhen-Ya

Author_Institution

Radio Dept., Southeastern Univ., Nanjing, China

fYear

1989

Firstpage

189

Lastpage

192

Abstract

Various existing multidimensional system identification theories and techniques are reviewed. Particular attention is given to various modeling and parameter estimation techniques. State space, conditional Markovian simultaneous autoregressive, and finite-order autoregressive moving average methods and their various variants are discussed. Maximum-likelihood, least-squares, and other commonly used techniques are also studied

Keywords

Markov processes; least squares approximations; multidimensional systems; parameter estimation; state-space methods; conditional Markovian simultaneous autoregressive methods; finite-order autoregressive moving average methods; least-squares methods; maximum likelihood methods; multidimensional system identification; parameter estimation techniques; state space methods; Difference equations; Finite difference methods; Gaussian noise; Maximum likelihood estimation; Multidimensional systems; Parameter estimation; Parametric statistics; Partial differential equations; Predictive models; State-space methods;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrotechnical Conference, 1989. Proceedings. 'Integrating Research, Industry and Education in Energy and Communication Engineering', MELECON '89., Mediterranean

Conference_Location

Lisbon

Type

conf

DOI

10.1109/MELCON.1989.50014

Filename

50014