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Titlebook: Advances in Neuromorphic Hardware Exploiting Emerging Nanoscale Devices; Manan Suri Book 2017 Springer (India) Pvt. Ltd. 2017 Low-power Co

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21#
發(fā)表于 2025-3-25 07:07:15 | 只看該作者
Compactifications of Symmetric Spacesic weight resolution and the robustness to device variability of the network have been investigated. Statistical evaluation of device variability is obtained on a 16?kbit OxRAM memory array integrated into advanced 28?nm CMOS technology.
22#
發(fā)表于 2025-3-25 10:48:55 | 只看該作者
Yves Guivarc’h,Lizhen Ji,J. C. Taylornaptic behavior in densely packed crossbar arrays suitable for on-chip learning. We discuss our recent research investigating the characteristics needed from such nonvolatile memory elements for implementation of high-performance ANNs. We describe experiments on a 3-layer perceptron network with 164
23#
發(fā)表于 2025-3-25 11:45:43 | 只看該作者
https://doi.org/10.1007/0-8176-4466-0r and complexity/area. Another challenge is realizing an area- and power-efficient implementation of the electronic neuron. A leaky integrate-and-fire (LIF) neuron has been implemented using analog and digital circuits which are highly power and area inefficient. To improve area and power efficiency
24#
發(fā)表于 2025-3-25 16:11:24 | 只看該作者
25#
發(fā)表于 2025-3-25 23:35:10 | 只看該作者
https://doi.org/10.1007/0-8176-4466-0 the input. This theoretical analysis allows interpreting how STDP differs for several device physics and why it is robust to device mismatch. It can also provide guidelines for designing STDP-based learning systems.
26#
發(fā)表于 2025-3-26 01:05:23 | 只看該作者
Hardware Spiking Artificial Neurons, Their Response Function, and Noises,Overview:
27#
發(fā)表于 2025-3-26 08:21:29 | 只看該作者
28#
發(fā)表于 2025-3-26 11:19:56 | 只看該作者
1867-4925 rasitic trade-offs, and complex real-world applications. The book is suited for both advanced researchers and students interested in the field..978-81-322-3890-4978-81-322-3703-7Series ISSN 1867-4925 Series E-ISSN 1867-4933
29#
發(fā)表于 2025-3-26 16:32:19 | 只看該作者
1867-4925 script in the field of neuromorphic hardware.Places major em.This book covers all major aspects of cutting-edge research in the field of neuromorphic hardware engineering involving emerging nanoscale devices. Special emphasis is given to leading works in hybrid low-power CMOS-Nanodevice design. The
30#
發(fā)表于 2025-3-26 17:58:00 | 只看該作者
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