Deep Learning Classifiers with Memristive Networks

TRAMA

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.

SOMMARIO

Available in MS

AUTORE

ALTRE INFORMAZIONI

• Condizione: Nuovo
• ISBN: 9783030145224
• Collana: Modeling and Optimization in Science and Technologies
• Dimensioni: 235 x 155 mm
• Formato: Copertina rigida
• Illustration Notes: XIII, 213 p. 124 illus., 102 illus. in color.
• Pagine Arabe: 213
• Pagine Romane: xiii