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Weighted Radial Basis Functions for improved pattern recognition and signal processing

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Abstract

The paper describes an improved version of the Radial Basis Function algorithm, which integrates the advantages of Multi-Layer Perceptrons and Radial Basis Functions alone. The proposed paradigm is more general in nature, since it has the other two as particular subcases. It finds applications in several pattern recognition and classification tasks. Furthermore it can also be used as a method to map Fuzzy Inference Systems on Artificial Neural Networks.

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Authors and Affiliations

  1. Dipartimento di Ingegneria dell'Informazione, Universita di Pisa, Via Diotisalvi 2, 1-56126, Pisa, Italy

    Leonardo M. Reyneri

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  1. Leonardo M. Reyneri
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Reyneri, L.M. Weighted Radial Basis Functions for improved pattern recognition and signal processing. Neural Process Lett 2, 2–6 (1995). https://doi.org/10.1007/BF02311571

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  • DOI: https://doi.org/10.1007/BF02311571

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