SpringerBriefs in Computational Intelligence : Analog Integrated Circuit Design under PVT Conditions : Efficient Reinforcement and Transfer Learning Techniques (SpringerBriefs in Applied Sciences and Technology)

Oliveira Paiva, Pedro Alberto/ Mota da Costa, José/ Pedro Ponte/ de Azevedo, Filipe Parrado

Springer, Berlin; Springer（2026/07発売）

• 製本 Paperback:紙装版/ペーパーバック版
• 商品コード 9783032194084

Full Description

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. It first examines multiple reinforcement‑learning‑based strategies for embedding PVT conditions directly into modern sizing flows, clarifying their conceptual differences and practical implications. 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. Together, these chapters provide a grounded overview of current techniques and ongoing developments in automated analog IC design.

Contents

Chapter 1 Introduction.- Chapter 2 State-of-the-Art.- Chapter 3 PVT Corner Conditions within Reinforcement Learning-based Analog IC Sizing.- Chapter 4 PVT Corner Analog IC Sizing Optimizations Boosted by ANN[1]based Performance Regressors and Transfer Learning.