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A reconfigurable fuzzy neural network with in-situ learning

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3 Author(s)
Pedrycz, W. ; Dept. of Electr. & Comput. Eng., Manitoba Univ., Winnipeg, Man., Canada ; Hart Poskar, C. ; Czerowski, P.J.

Our reconfigurable fuzzy processor (RFP) implements both aggregative and referential operations. Its architecture combines structural and parametric flexibility in a network implementing RFPs as a collection of fuzzy neurons. A fuzzy neural network using a bidirectionally linked series of shared buses facilitates a modular and scalable design environment for the RFP. An appropriate interface, separate from the RFP neuron itself, promotes the reuse of the neuron design with alternative interconnection networks

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Micro, IEEE  (Volume:15 ,  Issue: 4 )