State of system approximation for stochastic systems

Author

Stubberud, A.R. ; Perryman, P.C.

Author_Institution

Dept. of Electr. & Comput. Eng., California Univ., Irvine, CA, USA

Volume

2

fYear

1997

fDate

2-4 Jul 1997

Firstpage

711

Abstract

This paper describes a new contribution to stochastic, nonlinear system approximation. An approach to approximating stochastic systems is described by which the difficulties associated with the erratic behavior of sample functions are circumvented. This new approximation criterion is called uniform in-probability approximation, where the probability of the absolute approximation error exceeding a prescribed ε>0 is uniformly less than a prescribed probability p

Keywords

approximation theory; autoregressive moving average processes; error analysis; nonlinear systems; probability; signal processing; state estimation; stochastic systems; absolute approximation error; fading memory systems; input signals; nonlinear system approximation; sample functions; stochastic systems; system state approximation; uniform in-probability approximation; Approximation error; Autoregressive processes; Concrete; Linear approximation; Linear systems; Mathematical model; Modeling; Nonlinear systems; Stochastic systems; Transfer functions;

fLanguage

English

Publisher

ieee

Conference_Titel

Digital Signal Processing Proceedings, 1997. DSP 97., 1997 13th International Conference on

Conference_Location

Santorini

Print_ISBN

0-7803-4137-6

Type

conf

DOI

10.1109/ICDSP.1997.628451

Filename

628451