Synthesis Lectures on Engineering, Science, and Technology: Learning, Architectures and Large-Scale Systems

Yang, Shuangming; Chen, Badong

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.

Details

Published by: Springer

Publication Date: 2024-05-15

Format: Hardcover

ISBN-13: 9783031578724

DOI: 10.1007/978-3-031-57873-1

Dimensions: 240cm x168cm

Pages: 239