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Deep Learning Classifiers with Memristive Networks: Theory and Applications

by Alex Pappachen James
Save 35% Save 35%
Current price ₹12,354.00
Original price ₹19,005.00
Original price ₹19,005.00
Original price ₹19,005.00
(-35%)
₹12,354.00
Current price ₹12,354.00

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Book cover type: Hardcover
  • ISBN13: 9783030145224
  • Binding: Hardcover
  • Subject: N/A
  • Publisher: Springer
  • Publisher Imprint: Springer
  • Publication Date:
  • Pages: 213
  • Original Price: EUR 169.99
  • Language: English
  • Edition: 2020
  • Item Weight: 499 grams
  • BISAC Subject(s): Artificial Intelligence / Computer Vision & Pattern Recognition, Data Science / Data Analytics, and Software Development & Engineering / Computer Graphics

From the Back Cover

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.

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