Abstract
A simple algorithmic solution is developed for the discrete time, nonlinear, system identification problem based on a stochastic approximation method. The method is applicable to the noisy, as well as the noiseless, input-output measurement case. A minimal statistical knowledge of the noise and input sequences is required for this method; also, the algorithm is very easy to program. The proof of convergence for the algorithm is given along with some experimental results obtained from some control system input-output data.
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