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Energy-Efficient Devices and Circuits for Neuromorphic Computing

Specificaties
Paperback, blz. | Engels
Elsevier Science | e druk, 2025
ISBN13: 9780443299810
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Elsevier Science e druk, 2025 9780443299810
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Samenvatting

Energy-Efficient Devices and Circuits for Neuromorphic Computing is an important contribution to this field, covering topics from neuron dynamics to energy-efficient CMOS devices and circuits. The book delves into theoretical analysis of learning processes in spiking neural networks, two-terminal neuromorphic devices, material-engineered neuromorphic devices, and novel biomimetic Si devices. It offers insights into the latest developments in non-volatile memory crossbar arrays and emerging post-CMOS devices. Overall, it provides a comprehensive overview of energy-efficient neuromorphic computing architecture. This book is an essential resource for researchers, engineers, and students working in neuromorphic computing and energy-efficient electronics.

Specificaties

ISBN13:9780443299810
Taal:Engels
Bindwijze:Paperback

Inhoudsopgave

1. Biological neural systems NEW<br>2. Fundamentals of neuron dynamics and Neural Networks NEW<br>3. Foundations, recent developments and applications of spiking neural networks (SNNs)<br>4. Training and learning processes of SNNs<br>5. Introduction to Neuromorphic Computing<br>6. The Need for Energy Efficiency in Neuromorphic Computing v Review of Neuromorphic devices and Circuits<br>7. Energy-efficient devices for Neuromorphic computing<br>8. Novel biomimetic devices for energy efficient synapses and neurons OLD<br>9. Analog and Digital CMOS circuits for Energy Efficient Neuromorphic Computing<br>10. Energy-efficient Neuromorphic computing systems with emerging post-CMOS devices<br>11. Energy Efficient Neuromorphic Computing Architectures and Processing<br>12. Nonvolatile memory crossbar arrays for energy efficient neuromorphic computing<br>13. Energy Efficient Neuromorphic Vision Systems<br>14. Neuromorphic sensors and in-sensor computing<br>15. Practical Applications of Energy-Efficient Neuromorphic Computing<br>16. Current and future challenges of Neuromorphic Computing

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        Energy-Efficient Devices and Circuits for Neuromorphic Computing