A Heuristic Review on Analog Performance and Accomplishment of Activation Functions at RTL Level

Abstract

In this article, the behavior of many functional activities used for Artificial Neural Networks (ANNs) study is demonstrated together with their similar performance under transistor conditions. ANN plays an important role in computer science, technology, machine learning, automation, speech and voice processing. The accuracy of any automated device largely depends on ANN training. Therefore, choosing an appropriate operating system affects the performance of the entire system. Performing operational movements at the transistor levels with low power, latency, and power requirements without adjusting their properties is a major challenge. Process actions are performed on an analog or digital one. Analog performance simulations are clearly demonstrated in this article, as the field and power limit for simulation applications is greater than for digital applications. The efficiency of the operating system relies on the % of errors between its manufacture and quality.