Review on Analog Circuit Optimization Using Deep Learning Algorithm

Within many circumstances, analog circuits are made up of intricate pairings of op-amps, resistors, capacitors, and several other fundamental electrical devices. Making anything as completely flawless, usable, or beneficial as feasible is known as optimization. Recent developments in very large-scale integration (VLSI) techniques have made it possible to create sophisticated integrated circuits and systems. When it comes to aspects and areas in wide variations, analog devices are a significant part of integrated systems. On the other hand, analog devices play an essential role in modern system architecture. In this article, we reviewed a wide range of different optimization approaches in deep learning (DL), analog circuit optimization, and its relevant applications. In addition, significant criteria such as efficiency, latency, performance, and accuracy are being considered when confirming the outcome. As a direct consequence of this, the efficiency of deep learning optimization for analog circuits may be evaluated.