Description

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