Abstract
In this paper we develop the Wiener functional for an N-level uniformly distributed discrete random process for use in non-linear system identification. We show that the kernels of the functional may be estimated using cross correlation in a manner equivalent to that developed by Lee and Schetzen for Gaussian processes. The uniformly distributed process provides more power to the systen being studied than does a Gaussian process with the same amplitude ranne and is easy to generate on a dioital computer.
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