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Based on the filtering theory, we present a filtering based recursive least squares algorithm for a class of Wiener nonlinear systems. The basic idea is to use an estimated noise transfer function to filter the input-ouput data, to obtain two identification models containing the parameters of the system model and the noise model, respectively, and to(More)
This paper considers the state and parameter estimation problem of a state-delay system. On the basis of the stochastic gradient algorithm (i.e., the gradient based search estimation algorithm), this extends the scalar innovation into an innovation vector and presents a multi-innovation gradient parameter estimation algorithm for a state-space system with(More)
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