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The neural networks based on radial basis functions (RBF) represent a class of neural networks that are especially used for approximating functions, interpolations, regressions and classifications. There are feedforward networks, but their operation is different. The RBF neural networks have a multitude of applications: models recognition, medical classifications (very useful for deciding the diagnostic), fuzzy systems or function interpolation.

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Superior-Order Approximation Functions for Generating Radial Basis Activation Functions

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  • 发表日期：

    2025年

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  • Cosmin Radu Popa

摘要

The neural networks based on radial basis functions (RBF) represent a class of neural networks that are especially used for approximating functions, interpolations, regressions and classifications. There are feedforward networks, but their operation is different. The RBF neural networks have a multitude of applications: models recognition, medical classifications (very useful for deciding the diagnostic), fuzzy systems or function interpolation.