Overview

This book delivers a focused, technical exploration of automated analog and RF integrated circuit sizing under process, voltage, and temperature variations, guiding readers through foundational concepts, current methodologies, and advanced machine learning driven approaches.

Reinforcement Learning Strategies

It first examines multiple reinforcement learning based strategies for embedding PVT conditions directly into modern sizing flows, clarifying their conceptual differences and practical implications.

Deep Learning Approaches

It then explores a complementary deep learning assisted approach that leverages ANN based performance regressors, transfer learning, and adaptive refinement to accelerate simulation driven optimization without requiring extensive corner specific datasets.

Current Techniques and Developments

Together, these chapters provide a grounded overview of current techniques and ongoing developments in automated analog IC design.