This book provides a holistic view of modelling for analogue, high frequency, mixed signal, and heterogeneous systems for designers working towards improving efficiency, reducing design times, and addressing the challenges of representing aging, variability, and other technical challenges at the nanometre scale.

• Chapter 1: Introduction


• Part I: Fundamentals of modelling methodologies
  
  
  • Chapter 2: Response surface modeling
  
  
  • Chapter 3: Machine learning
  
  
  • Chapter 4: Data-driven and physics-based modeling
  
  
  • Chapter 5: Verification of modeling: metrics and methodologies
  
  
  
  
  
• Part II: Applications in analogue integrated circuit design
  
  
  • Chapter 6: An overview of modern, automated analog circuit modeling methods: similarities, strengths, and limitations
  
  
  • Chapter 7: On the usage of machine-learning techniques for the accurate modeling of integrated inductors for RF applications
  
  
  • Chapter 8: Modeling of variability and reliability in analog circuits
  
  
  • Chapter 9: Modeling of pipeline ADC functionality and nonidealities
  
  
  • Chapter 10: Power systems modelling
  
  
  • Chapter 11: A case study for MEMS modelling: efficient design and layout of 3D accelerometer by automated synthesis
  
  
  • Chapter 12: Spintronic resistive memories: sensing schemes
  
  
  • Chapter 13: Conclusion