On the Application of the Parzen-Type Kernel Probabilistic Neural Network and Recursive Least Squares Method for Learning in a Time-Varying Environment

This paper presents the Parzen kernel-type regression neural network in combination with recursive least squares method to solve problem of learning in a time-varying environment. Sufficient conditions for convergence in probability are given. Simulation experiments are presented and discussed.

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