Abstract
In this paper we present KERNEL, a neuro-fuzzy system for the extraction of knowledge directly from data, and a toolbox developed in the Matlab environment for its implementation. The KERNEL system belongs to the novel approach which concerns the use and representation of explicit knowledge within the neurocomputing paradigm: the Knowledge Based Neurocomputing. A specific neural network is designed, that reflects in its topology the structure of the fuzzy inference model on which is based the KERNEL system. A well-known system identification benchmark is used as illustrative example.
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© 2002 Springer-Verlag Berlin Heidelberg
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Castellano, G., Castiello, C., Fanelli, A.M. (2002). KERNEL: A Matlab Toolbox for Knowledge Extraction and Refinement by NEural Learning. In: Sloot, P.M.A., Hoekstra, A.G., Tan, C.J.K., Dongarra, J.J. (eds) Computational Science — ICCS 2002. ICCS 2002. Lecture Notes in Computer Science, vol 2329. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46043-8_98
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DOI: https://doi.org/10.1007/3-540-46043-8_98
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