NEUROMORPHIC COMPUTING – A PRIMER

by Swetha D, Dhanushmathi S, NARASIMHAN B

Neuromorphic Computing - A Primer takes readers on an exciting journey into the rapidly evolving field of brain-inspired computing. With its 40 carefully structured chapters, this book bridges the gap between traditional and neuromorphic paradigms, offering insights into the revolutionary potential of systems modeled after the human brain. Starting with foundational concepts, it delves into the historical evolution of neuromorphic systems and contrasts them with conventional computing approaches. Readers are introduced to neural dynamics, spiking neural networks, and the critical role of synaptic plasticity, with a focus on cutting-edge technologies like IBM's TrueNorth, Intel’s Loihi, and Spinnaker. The book explores bio-inspired learning algorithms, event-driven architectures, and innovative hardware components such as memristors, alongside their applications in robotics, healthcare, and autonomous vehicles. It highlights the power of neuromorphic systems in edge AI, IoT, real-time pattern recognition, and cybersecurity, while emphasizing energy-efficient computing models. With detailed discussions on mixed-signal designs, temporal coding, and brain-machine interfaces, this primer is a treasure trove for engineers, researchers, and technology enthusiasts eager to unlock the future of computing. Whether your interest lies in advancing AI capabilities, simulating cognitive processes, or transforming data centers, this comprehensive guide offers the technical depth and broad vision needed to understand and shape the frontier of neuromorphic innovation.

279 pages, Kindle Edition

Published January 1, 2025