Deep Learning Classifiers with Memristive Networks: Theory and Applications

James, Alex Pappachen

  • 出版商: Springer
  • 出版日期: 2019-04-17
  • 售價: $7,108
  • 貴賓價: 9.5$6,753
  • 語言: 英文
  • 頁數: 213
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 3030145220
  • ISBN-13: 9783030145224
  • 相關分類: DeepLearning 深度學習

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商品描述

This book introduces readers to the fundamentals of deep neural network architectures, with a special emphasis on memristor circuits and systems. At first, the book offers an overview of neuro-memristive systems, including memristor devices, models, and theory, as well as an introduction to deep learning neural networks such as multi-layer networks, convolution neural networks, hierarchical temporal memory, and long short term memories, and deep neuro-fuzzy networks. It then focuses on the design of these neural networks using memristor crossbar architectures in detail. The book integrates the theory with various applications of neuro-memristive circuits and systems. It provides an introductory tutorial on a range of issues in the design, evaluation techniques, and implementations of different deep neural network architectures with memristors.