Multiple Threshold Neural Logic

Part of Advances in Neural Information Processing Systems 10 (NIPS 1997)

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Vasken Bohossian, Jehoshua Bruck


We introduce a new Boolean computing element related to the Lin(cid:173) ear Threshold element, which is the Boolean version of the neuron. Instead of the sign function, it computes an arbitrary (with poly(cid:173) nornialy many transitions) Boolean function of the weighted sum of its inputs. We call the new computing element an LT M element, which stands for Linear Threshold with Multiple transitions. The paper consists of the following main contributions related to our study of LTM circuits: (i) the creation of efficient designs of LTM circuits for the addition of a multiple number of integers and the product of two integers. In particular, we show how to compute the addition of m integers with a single layer of LT M elements. (ii) a proof that the area of the VLSI layout is reduced from O(n2 ) in LT circuits to O(n) in LTM circuits, for n inputs symmetric Boolean functions, and (iii) the characterization of the computing power of LT M relative to LT circuits.