Learning in Energy-Efficient Neuromorphic Computing

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Algorithm and Architecture Co-Design

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Algorithm and Architecture Co-Design

Explains current co-design and co-optimization methodologies for building hardware neural networks and algorithms for machine learning applications

This book focuses on how to build energy-efficient hardware for neural networks with learning capabilities--and provides co-design and co-optimization methodologies for building hardware neural networks that can learn. Presenting a complete picture from high-level algorithm to low-level implementation details, Learning in Energy-Efficient Neuromorphic Computing: Algorithm and Architecture Co-Design also covers many fundamentals and essentials in neural networks (e.g., deep learning), as well as hardware implementation of neural networks.

The book begins with an overview of neural networks. It then discusses algorithms for utilizing and training rate-based artificial neural networks. Next comes an introduction to various options for executing neural networks, ranging from general-purpose processors to specialized hardware, from digital accelerator to analog accelerator. A design example on building energy-efficient accelerator for adaptive dynamic programming with neural networks is also presented. An examination of fundamental concepts and popular learning algorithms for spiking neural networks follows that, along with a look at the hardware for spiking neural networks. Then comes a chapter offering readers three design examples (two of which are based on conventional CMOS, and one on emerging nanotechnology) to implement the learning algorithm found in the previous chapter. The book concludes with an outlook on the future of neural network hardware.

Includes cross-layer survey of hardware accelerators for neuromorphic algorithms Covers the co-design of architecture and algorithms with emerging devices for much-improved computing efficiency Focuses on the co-design of algorithms and hardware, which is especially critical for using emerging devices, such as traditional memristors or diffusive memristors, for neuromorphic computing Learning in Energy-Efficient Neuromorphic Computing: Algorithm and Architecture Co-Design is an ideal resource for researchers, scientists, software engineers, and hardware engineers dealing with the ever-increasing requirement on power consumption and response time. It is also excellent for teaching and training undergraduate and graduate students about the latest generation neural networks with powerful learning capabilities.

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مغایرت عنوان کتاب با توضیحات و تصویر جلد
عدم رعایت حقوق نشر طبق قوانین جمهوری اسلامی ایران
محتوای مستهجن
توهین به قومیتها و محتوای نژادپرستی
توهین به اقیلیتهای مذهبی
اهانت به مقامات سیاسی و مذهبی
اشاعه ی کودک آزاری
سایر موارد

بستن

فرمت کتاب

ebook

زبان

english

تاریخ انتشار

2019

نویسنده

Pinaki Mazumder

ناشر

Wiley-IEEE Press

شابک

9781119507383

20,000 تومان

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خرید کتاب Learning in Energy-Efficient Neuromorphic Computing

Learning in Energy-Efficient Neuromorphic Computing

گزارش تخلف

فرمت کتاب

ebook

زبان

english

تاریخ انتشار

2019

نویسنده

ناشر

شابک

دیدگاه کاربران