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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.
Produkteigenschaften
- Artikelnummer: 9783030145224
- Medium: Buch
- ISBN: 978-3-030-14522-4
- Verlag: Springer International Publishing
- Erscheinungstermin: 17.04.2019
- Sprache(n): Englisch
- Auflage: 1. Auflage 2020
- Serie: Modeling and Optimization in Science and Technologies
- Produktform: Gebunden
- Gewicht: 512 g
- Seiten: 213
- Format (B x H x T): 160 x 241 x 18 mm
- Ausgabetyp: Kein, Unbekannt