Mixed Signal

Mixed-signal (analog/digital) circuit design integrates analog and digital components to leverage the strengths of both, aiming for improved efficiency, accuracy, and functionality in various applications. Current research focuses on enhancing robustness against noise and variations using techniques like denoising blocks in neural networks and adaptive number representations, as well as automating design processes through machine learning models such as Bayesian neural networks and artificial neural networks for faster and more efficient circuit synthesis. This field is crucial for advancing neuromorphic computing, improving the reliability of safety-critical systems (e.g., automotive), and enabling more efficient and complex integrated circuits.