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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TSH582

Substance-Abuse

Learning in Neuromorphic Systems,phisticated property that makes energy-efficient computation possible is the distinct sparse communication among many spiking neurons. The primary goal of neuromorphic hardware is to emulate brain-like neural networks to solve real-world problems. However, training on neuromorphic systems is challen

FRAUD

Emerging Memory Devices for Neuromorphic Systems, emulate biological synapses. Recently, numerous efforts have been made to realize artificial synapses using post-CMOS devices, including resistive random access memory (ReRAM), ferroelectric field-effect transistor (FeFET), phase change memory devices, magnetoresistive random access memory (MRAM),

Bother

Venules

PALSY

Reconfigurable Neuromorphic Computing System,ieving the learning and adaptability of the human brain. The weight of a synapse shows connection strength between the two neurons linked by that synapse. Spiking neural networks are used in applications ranging from vision systems to brain-computer interfaces. However, the design of such systems ha

Kinetic

Case Study: Real Hardware-Software Design of 3D-NoC-Based Neuromorphic System,D-ICs biological brain’s three-dimensional structure. The platform enables high integration density and slight spike delay of spiking networks and features a scalable design. R-NASH is a design based on the Through-Silicon-Via technology, facilitating spiking neural network implementation on cluster

思考

Survey of Neuromorphic Systems,of research works in neuromorphic computing systems. First, the chapter gives the motivations for neuromorphic computing, then describes significant research works in the field. These works are categorized as software emulation, digital hardware, and analog and mixed-signal hardware approaches. This

鎮(zhèn)壓

od and organization of neuromorphic architecture.Presents a This book focuses on neuromorphic computing principles and organization and how to build fault-tolerant scalable hardware for large and medium scale spiking neural networks with learning capabilities. In addition, the book describes in a co