Importance

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Abstract

Nodal outputs are discretized to values of S2.sup.n where n is an integer and S is equal to +1 or -1. During forward propagation, this offers the advantage of forming a product of a nodal output and a weight using a simple shift operation rather than a multiply operation. Replacing multiply operations with shift operations through out a neural network improves response times and permits building larger networks that have broader applicability. Training is also improved by increasing the efficiency of backward propagation. The multiplications involved in backward propagation are reduced To shift operations by discretizing the errors associated with each node so that they are represented as 2.sup.n where n is an integer and S is equal to +1 or -1.

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First Claim