Titlebook: Neuromorphic Computing Principles and Organization; Abderazek Ben Abdallah,Khanh N. Dang Textbook 2022 The Editor(s) (if applicable) and T

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Textbook 2022piking neural networks with learning capabilities. In addition, the book describes in a comprehensive way the organization and how to design a spike-based neuromorphic system to perform network of spiking neurons communication, computing, and adaptive learning for emerging AI applications. The book

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Survey of Neuromorphic Systems,esearch works in the field. These works are categorized as software emulation, digital hardware, and analog and mixed-signal hardware approaches. This chapter aims to provide an exhaustive review of the research conducted in neuromorphic computing and illuminate the gaps in the field where new research is needed.

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Reconfigurable Neuromorphic Computing System,e implements a spiking neural network that can be reconfigured to recover from faults with suitable methods that use an FPGA without being dependent on FPGA intellectual property. This approach makes possible its implementation in Application-Specific Integrated Circuits (ASICs).