Boris Murmann – författare

Discover a fresh approach to efficient and insight-driven analog integrated circuit design in nanoscale-CMOS with this hands-on guide. Expert authors present a sizing methodology that employs SPICE-generated lookup tables, enabling close agreement between hand analysis and simulation. This enables the exploration of analog circuit tradeoffs using the gm/ID ratio as a central variable in script-based design flows, and eliminates time-consuming iterations in a circuit simulator. Supported by downloadable MATLAB code, and including over forty detailed worked examples, this book will provide professional analog circuit designers, researchers, and graduate students with the theoretical know-how and practical tools needed to acquire a systematic and re-use oriented design style for analog integrated circuits in modern CMOS.

With the advent of powerful digital signal processing in portable electronic applications, we have seen a growing, unsatisfied demand for power efficient, high-speed and high-resolution analog-to-digital converters (ADCs). While technology scaling has led to revolutionary gains in digital computing power and energy efficiency, progress in analog-to-digital conversion interfaces has been comparatively slow. Digitally Assisted Pipeline ADCs: Theory and Implementation explores the opportunity to reduce ADC power dissipation by leveraging digital signal processing capabilities in fine line integrated circuit technology. The described digitally assisted pipelined ADC uses a statistics-based system identification technique as an enabling element to replace precision residue amplifiers with simple open-loop gain stages. The digital compensation of analog circuit distortion eliminates one key factor in the classical noise-speed-linearity constraint loop and thereby enables a significant power reduction. Digitally Assisted Pipeline ADCs: Theory and Implementation describes in detail the implementation and measurement results of a 12-bit, 75-MSample/sec proof-of-concept prototype. The Experi

Digitally Assisted Pipeline ADCs: Theory and Implementation explores the opportunity to reduce ADC power dissipation by leveraging digital signal processing capabilities in fine line integrated circuit technology. The described digitally assisted pipelined ADC uses a statistics-based system identification technique as an enabling element to replace precision residue amplifiers with simple open-loop gain stages. The digital compensation of analog circuit distortion eliminates one key factor in the classical noise-speed-linearity constraint loop and thereby enables a significant power reduction. Digitally Assisted Pipeline ADCs: Theory and Implementation describes in detail the implementation and measurement results of a 12-bit, 75-MSample/sec proof-of-concept prototype. The Experimental converter achieves power savings greater than 60% over conventional implementations. Digitally Assisted Pipeline ADCs: Theory and Implementation will be of interest to researchers and professionals interested in advances of state-of-the-art in A/D conversion techniques.

This book describes techniques for time-interleaving a number of analog-to-digital data converters to achieve demanding bandwidth requirements.  Readers will benefit from the presentation of a low-power solution that can be used in actual products, while alleviating the time-varying signal artifacts that typically arise when implementing such a system architecture.

This book describes techniques for time-interleaving a number of analog-to-digital data converters to achieve demanding bandwidth requirements.  Readers will benefit from the presentation of a low-power solution that can be used in actual products, while alleviating the time-varying signal artifacts that typically arise when implementing such a system architecture.

In this book, a global team of experts from academia, research institutes and industry presents their vision on how new nano-chip architectures will enable the performance and energy efficiency needed for AI-driven advancements in autonomous mobility, healthcare, and man-machine cooperation. Recent reviews of the status quo, as presented in CHIPS 2020 (Springer), have prompted the need for an urgent reassessment of opportunities in nanoelectronic information technology. As such, this book explores the foundations of a new era in nanoelectronics that will drive progress in intelligent chip systems for energy-efficient information technology, on-chip deep learning for data analytics, and quantum computing. Given its scope, this book provides a timely compendium that hopes to inspire and shape the future of nanoelectronics in the decades to come.