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This work demonstrates an application of the Parametric CMAC (P-CMAC) Network --a neural structure derived from Albus's CMAC algorithm and Takagi-Sugeno-Kang parametric fuzzy inference systems. It resembles the original CMAC proposed by James Albus in the sense that it is a local network, (i.e., for a given input vector); only a few of the networks nodes (or neurons) will be active and will effectively contribute to the corresponding network output. The internal mapping structure is built indoi:10.1109/tia.2004.836135 fatcat:f2fejezuzra47evifi4kmls2se