| 书目名称 | Deep Learning Classifiers with Memristive Networks | | 副标题 | Theory and Applicati | | 编辑 | Alex Pappachen James | | 视频video | | | 概述 | Offers an introduction to deep neural network architectures.Describes in detail different kind of neuro-memristive systems, circuits and models.Shows how to implement different kind of neural networks | | 丛书名称 | Modeling and Optimization in Science and Technologies | | 图书封面 |  | | 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.. | | 出版日期 | Book 2020 | | 关键词 | Neuro-memristive Computing; Memristive Crossbar Arrays; Memristor Models; Memristor Materials; Deep Lear | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-030-14524-8 | | isbn_ebook | 978-3-030-14524-8Series ISSN 2196-7326 Series E-ISSN 2196-7334 | | issn_series | 2196-7326 | | copyright | Springer Nature Switzerland AG 2020 |
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发表于 2025-3-21 17:21:06
