Yang S., Chen B. Neuromorphic Intelligence: Learning, Architectures and Large-Scale Systems

Springer Cham, 2024. — 239 p. — (Synthesis Lectures on Engineering, Science, and Technology). — eBook ISBN: 978-3-031-57873-1.Discusses neuromorphic intelligence, which serves as a foundation for compact, low-power brain-inspired systems.
Includes learning algorithms, architecture design, and implementation of large-scale systems.
Offers a holistic view of the field, allowing readers to gain a deep understanding of the subject.This book provides a valuable resource on the design of neuromorphic intelligence, which serves as a computational foundation for building compact and low-power brain-inspired intelligent systems. The book introduces novel spiking neural network learning algorithms, including spike-based learning based on the multi-compartment model and spike-based learning with information theory. These offer important insights and academic value for readers to grasp the latest advances in neural-inspired learning. Additionally, the book presents insights and approaches to the design of scalable neuromorphic architectures, which are crucial foundations for achieving highly cognitive and energy-efficient computing systems. Furthermore, the book introduces representative large-scale neuromorphic systems and reviews several recently implemented large-scale digital neuromorphic systems by the authors, providing corresponding application scenarios.True PDF