Title :
The discrete Wiener model for representation of nonGaussian stochastic processes
Author :
Therrien, Charles W. ; Hashad, Atalla I.
Author_Institution :
Dept. of Electr. & Comput. Eng., Naval Postgraduate Sch., Monterey, CA, USA
Abstract :
The Wiener (1958) model for nonlinear systems is capable of representing a very large class of random processes. In this paper the discrete-time form of this model is developed and it is shown how the moments of any order can be computed for an arbitrary nonlinear process represented by the Wiener model. The moments are expressed in terms of certain normalized “correlation functions” that have a simple and easily computable form. An explicit organized procedure for computing the moments of any order is presented and illustrated in an example
Keywords :
nonlinear systems; random processes; stochastic processes; discrete Wiener model; moments; nonGaussian stochastic processes representation; nonlinear process; nonlinear systems; normalized correlation functions; random processes; Convergence; Gaussian processes; Kernel; Linear systems; Memoryless systems; Multidimensional systems; Nonlinear systems; Polynomials; Random processes; Stochastic processes;
Conference_Titel :
Signals, Systems and Computers, 1993. 1993 Conference Record of The Twenty-Seventh Asilomar Conference on
Conference_Location :
Pacific Grove, CA
Print_ISBN :
0-8186-4120-7
DOI :
10.1109/ACSSC.1993.342554
