Title :
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
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;
Conference_Titel :
Digital Signal Processing Proceedings, 1997. DSP 97., 1997 13th International Conference on
Conference_Location :
Santorini
Print_ISBN :
0-7803-4137-6
DOI :
10.1109/ICDSP.1997.628451
