Rapid developments in semiconductor technology have substantially increased the
computational capability of computers. As a result of this and recent developments in theory …

Analog integrated circuit design is widely considered a time-consuming task due to the
acute dependence of analog performance on the transistors' and passives' dimensions. An …

The focus of this study is to predict curved crack FCG failure under variable amplitude load
effectively and accurately. Based on the artificial neural network (ANN) and FCG path/life …

Automated design of analog and radio-frequency circuits using supervised or reinforcement
learning from simulation data has recently been studied as an alternative to manual expert …

The existence of multi-dimensional tradeoffs among performance metrics is an impediment
to the development of reliable Electronic Design Automation (EDA) tools for the design of …

This paper proposes an efficient design technique for two commonly used VLSI circuits,
namely, CMOS current mirror load-based differential amplifier circuit and CMOS two-stage …

This paper proposes a novel adaptation of Machine Learning (ML) techniques based on
reinforcement learning for the resolution of analog sizing optimization problems. The paper …

Digital and analog devices and circuits are basic electronic components in the widest type of
electronic devices. In addition to consumer electronics markets, the IC industry more than …

This work investigates the application of artificial neural networks to predict transistor
dimensions in analog integrated circuits using semi-supervised learning. Traditionally …

This article explores the comparative optimizing efficiency between two PSO variants,
namely, Craziness based PSO (CRPSO) and PSO with an Aging Leader and Challengers …