Analog Computing

Moving Beyond Classical Logic

De: Ajit Singh

Narrado por: Virtual Voice

About the Book

"Analog Computing: Moving Beyond Classical Logic" is a comprehensive and accessible textbook designed to introduce undergraduate (B.Tech) and postgraduate (M.Tech) students of Computer Science and related engineering disciplines to the fascinating world of analog computing. As the limits of traditional digital computing become more apparent, especially in the context of energy-intensive AI applications, analog computing has re-emerged as a critical area of innovation. This book serves as a bridge between the historical foundations of the field and its cutting-edge, modern applications.
The pedagogical approach of this book is firmly rooted in the principles of emphasizing conceptual understanding, hands-on learning, and real-world problem-solving over rote memorization. The content is structured to be simple, relevant, and engaging, using intuitive examples and analogies to explain complex topics. The flow is logical and progressive, starting from the absolute basics and gradually building up to advanced concepts, making it suitable for both beginners and advanced learners.


Key Features:

1. Logical Progression: The ten chapters are structured to take the reader on a seamless journey from "what" and "why" to "how," covering fundamental principles, core components, circuit design, advanced architectures, and modern applications.
2. Hands-On Practical Approach: The book is rich with practical examples, circuit diagrams, and simulation exercises. Case studies of real-world analog computing systems from industry leaders provide valuable context.
3. Capstone DIY Project: The final chapter is a complete, step-by-step guide to building a working analog computer using common electronic components, allowing students to see the principles in action. This includes circuit diagrams, component lists, and complete code for interfacing (if required), with detailed explanations.
4. Focus on AI and Modern Applications: The book dedicates significant attention to the most relevant modern application of analog computing: energy-efficient AI. It covers neuromorphic architectures, in-memory computing, and other techniques at the forefront of AI hardware research.
5. Clarity and Simplicity: Every concept is explained in the simplest possible terms, supported by clear illustrations and real-life examples to ensure that the material is accessible to students from diverse backgrounds.


To Whom This Book Is For:

1. B.Tech/M.Tech Computer Science & Engineering Students: The primary audience for whom the book serves as a core or elective course textbook on computer architecture or emerging computing paradigms.
2. Electronics & Communication/Electrical Engineering Students: Students interested in circuit design, signal processing, and the physical implementation of computational systems.
3. Researchers and Academics: A valuable resource for those researching post-Moore's Law computing, neuromorphic engineering, and energy-efficient hardware.
4. Industry Professionals & AI Hardware Engineers: Engineers and designers working on developing specialized hardware (ASICs, FPGAs) for AI, IoT, and signal processing applications.
5. Hobbyists and DIY Enthusiasts: Individuals with an interest in electronics and computing who wish to explore a different paradigm of building computational machines.

Disclaimer: Earnest request from the Author.

Kindly go through the table of contents and refer kindle edition for a glance on the related contents.

Thank you for your kind consideration!