Optimum Nonlinear
نویسندگان
چکیده
| This paper is composed of two parts. The rst part surveys the literature regarding optimum nonlinear l-tering from the (continuous-time) stochastic analysis point of view, and the other part explores the impact of recent applications of neural networks (in a discrete-time context) to nonlinear ltering. In particular, the results obtained by using a regularized form of radial basis function (RBF) networks are presented in fair detail.
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