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Modelling Methodologies in Analogue Integrated Circuit Design

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Modelling methods for analogue circuit design

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AlbakiReads Editorial

Modelling methods for analogue circuit design

This edited technical volume connects the foundations of circuit modelling with methods used across analogue, high-frequency, mixed-signal and heterogeneous systems. Its opening chapters introduce the history and development of circuit design, then examine modelling approaches, accuracy and verification through theory and simple examples. The later, application-led chapters broaden the scope with case studies and topics including machine learning, data-driven and physics-based models, variability and reliability, pipeline ADCs, power systems, 3D accelerometer design and spintronic resistive-memory sensing. The book also addresses challenges associated with ageing and variability at nanometre scales, placing modelling methods in the context of practical design concerns.

Good fit for readers who enjoy

  • Circuit designers working with analogue, high-frequency or mixed-signal systems
  • Readers seeking technical coverage of modelling methods, accuracy and verification
  • Those interested in applications of machine learning and modelling to integrated-circuit design

Themes

Analogue integrated-circuit designModelling accuracy and verificationMachine learning and data-driven modellingVariability, reliability and ageingApplication-led circuit-design case studies

Based on publisher information and book metadata.

Book overview

Modelling Methodologies in Analogue Integrated Circuit Design 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.

The book begins by introducing the concept, history, and development of circuit design up to the present day. The first half of the book then covers various modelling methodologies and addresses model accuracy and verification. Modelling approaches are introduced theoretically along with simple examples to demonstrate the concepts. Later chapters approach modelling from the application point of view, including case studies from the vast domain of integrated circuit design.

Topics covered include response surface modeling; machine learning; data-driven and physics-based modeling; verification of modelling: metrics and methodologies; an overview of modern, automated analog circuit modeling methods; machine learning techniques for the accurate modeling of integrated inductors for RF applications; modeling of variability and reliability in analog circuits; modeling of pipeline ADC functionality and non-idealities; power systems modelling; case study - an efficient design and layout of a 3D accelerometer by automated synthesis; and sensing schemes for spintronic resistive memories.

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