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In this chapter, a method to obtain a stable algorithm is presented for the learning of a radial basis function neural network. The method consists of (1) the radial basis function neural network is linearized, (2) the algorithm for the learning of the radial basis function neural network is introduced, (3) stability of the mentioned technique is assured, (4) convergence of the suggested method is guaranteed, and (5) boundedness of parameters in the focused technique is assured. The abovementioned method is applied for the learning of two mechatronic processes.

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Uniform Stable Radial Basis Function Neural Network for the Prediction in Two Mechatronic Processes

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  • 发表日期：

    2025年

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  • Jose de Jesus Rubio

摘要

In this chapter, a method to obtain a stable algorithm is presented for the learning of a radial basis function neural network. The method consists of (1) the radial basis function neural network is linearized, (2) the algorithm for the learning of the radial basis function neural network is introduced, (3) stability of the mentioned technique is assured, (4) convergence of the suggested method is guaranteed, and (5) boundedness of parameters in the focused technique is assured. The abovementioned method is applied for the learning of two mechatronic processes.