Nonlinear Systems Identification Using the Volterra Model
نویسنده
چکیده
Nonlinear adaptive filtering techniques are widely used for the nonlinearities identification in manny applications. This paper investigates the performances of the Volterra estimator by considering a nonlinear system identification application. The Volterra estimator parameters are compared with those of a linear estimator. For the nonlinear estimator, based on a second order RLS Volterra filter, a new implementation is proposed. The experimental results show that the proposed Volterra identifier has better performances than the linear one. Different degrees of nonlinearity for the nonlinear system are considered.
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