Deep Learning Classifiers with Memristive Networks: Theory and Applications: 14 (Modeling and Optimization in Science and Technologies) - Hardcover

Hardcover

ISBN 10: 3030145220 ISBN 13: 9783030145224

Verlag: Springer, 2019

Inhaltsangabe

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.

Über diesen Titel

Über die Autorin bzw. den Autor

Von der hinteren Coverseite

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.

Details zur Ausgabe

• Verlag: Springer
• Erscheinungsdatum: 2019
• Sprache: Englisch
• ISBN 10: 3030145220
• ISBN 13: 9783030145224
• Einband: Tapa dura
• Auflage: 1
• Anzahl der Seiten: 228
• Herausgeber: James Alex Pappachen
• Kontakt zum Hersteller: Nicht verfügbar
• Verantwortliche Person: CMN Printpool Inh. Mathis Neumann; https://www.also.com/ec/cms5/en_6000/6000/index.jsp; ; Friedrich-Karl-Str. 9; Hamburg; Deutschland