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In this work, an alternative architecture of a pure analog artificial neural network is introduced. This includes circuits operating in the subthreshold region such as the Gaussian bell-shaped curve circuit, sigmoid function circuit, analog multiplier, and current comparator. The overall implementation consumes 1. 95 W and achieves an average accuracy of 94. 25%. An additional advantage is its ability to handle a large number of features. It is designed and verified in a TSMC 90nm CMOS process. Furthermore, post-layout results are compared both with software and with the literature. Based on these characteristics, it emerges as a promising candidate for robot execution failures systems.
Alimisis et al. (Sun,) studied this question.