Neuro-inspired computing using resistive synaptic devices

• Other Authors: Yu, Shimeng (Electrical engineer) (Editor)
• Format: Electronic eBook
• Language: English
• Published: Cham, Switzerland : Springer, 2017.
• Subjects: Neural computers.; elektronické knihy; electronic books
• ISBN: 9783319543130; 9783319543123
• Physical Description: 1 online resource (xi, 269 pages) : illustrations (some color)
• Access: Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty

This book summarizes the recent breakthroughs in hardware implementation of neuro-inspired computing using resistive synaptic devices. The authors describe how two-terminal solid-state resistive memories can emulate synaptic weights in a neural network. Readers will benefit from state-of-the-art summaries of resistive synaptic devices, from the individual cell characteristics to the large-scale array integration. This book also discusses peripheral neuron circuits design challenges and design strategies. Finally, the authors describe the impact of device non-ideal properties (e.g. noise, variation, yield) and their impact on the learning performance at the system-level, using a device-algorithm co-design methodology." Provides single-source reference to recent breakthroughs in resistive synaptic devices, not only at individual cell-level, but also at integrated array-level; " Includes detailed discussion of the peripheral circuits and array architecture design of the neuro-crossbar system; " Focuses on new experimental results that are likely to solve practical, artificial intelligent problems, such as image classification.