Energy-Efficient Devices and Circuits for Neuromorphic Computing

Energy-Efficient Devices and Circuits for Neuromorphic Computing by Farooq Ahmad Khanday is an essential guide for engineers, researchers and advanced students seeking practical, low-power solutions for next-generation computing. This authoritative volume brings clarity to the intersection of device physics and circuit design that powers neuromorphic systems — from spiking neural networks to event-driven edge AI.

Begin with a compelling overview of why energy efficiency is the linchpin of neuromorphic computing today, then dive into rigorous yet accessible explorations of technologies such as subthreshold CMOS, memristive devices, mixed-signal circuits, and asynchronous architectures. The book balances theoretical foundations with real-world design trade-offs, measurement techniques and power-accuracy considerations that matter in today’s IoT, robotics and mobile AI applications.

You’ll find hands-on guidance for optimizing circuits and devices to meet strict energy budgets, plus comparative analyses that help readers choose the right approach for specific application scenarios. Case studies and practical examples translate complex concepts into actionable design strategies, making this work invaluable for anyone developing neuromorphic chips or sensor-integrated systems.

Whether you’re building prototypes in a university lab or advancing low-power Books in industry, this book equips you to reduce power consumption without sacrificing performance. Globally relevant — from North America and Europe to Asia — it addresses the challenges facing modern hardware designers.

Add Energy-Efficient Devices and Circuits for Neuromorphic Computing by Farooq Ahmad Khanday to your professional library and start designing the energy-smart neuromorphic systems of tomorrow. Order your copy today.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.