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The CMAC is a neural net for computing real-valued functions. Conceptually, the CMAC maps a point in the function’s domain to a set of locations in an associative memory. Each location “contains” a weight, and the sum of the weights is taken to be the function’s value at that point. The overall process may be modeled as the multiplication of an input vector by an “association matrix.” This paper highlights...
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