Circuit Model

Circuit modeling research focuses on automating the design and analysis of electronic circuits, aiming to improve efficiency and accuracy compared to traditional methods. Current efforts leverage machine learning, particularly neural networks (like Transformers and LSTMs) and reinforcement learning, to generate circuit topologies, predict circuit behavior, and optimize designs based on various data sources (e.g., simulation results, impedance spectra). This work is significant for accelerating the design process for complex circuits in diverse applications, from analog integrated circuits to power systems, and improving the accuracy and efficiency of circuit simulations.