Neuromorphic Intelligence: Leaing, Architectures and Large-Scale Systems (Synthesis Lectures on Engineering, Science, and Technology)

by: Shuangming Yang (Author),Badong Chen(Author)

Publisher: Springer
Edition: 2024th

Publication Date: May 15, 2024

Language: English

Print Length: 258 pages

ISBN-10: 3031578724

ISBN-13: 9783031578724

Book Description

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 leaing algorithms, including spike-based leaing based on the multi-compartment model and spike-based leaing with information theory. These offer important insights and academic value for readers to grasp the latest advances in neural-inspired leaing. 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.
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 leaing algorithms, including spike-based leaing based on the multi-compartment model and spike-based leaing with information theory. These offer important insights and academic value for readers to grasp the latest advances in neural-inspired leaing. 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. Read more