Thursday, January 21, 2021

A Controlled Accuracy-Based Recursive Algorithm for Approximation of Sigmoid Activation

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Abstract

The sigmoid activation function is widely used in the development of neural networks. It is implemented in hardware development using an approximation scheme. In this paper, a piecewise linear (PWL) approximation scheme is developed as an accuracy controlled recursive algorithm. It uses a maximum allowable error as an input parameter and the least square method for finding the PWL function. The algorithm's accuracy is calculated with an absolute average and maximum error and compared to the state of the art. The approximation scheme's hardware implementation complexity is compared in terms of the number of PWL functions required. Results show that the proposed algorithm requires comparatively fewer PWL functions for the approximate sigmoid function for the specified accuracy.

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