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1. |
Record Nr. |
UNISA996394311903316 |
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Autore |
Byrd William |
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Titolo |
Parthenia, or, The maydenhead of the first musicke that euer was printed for the virginalls composed by three famous masters, William Byrd, Dr. John Bull, & Orlando Gibbons, gentilmen of His Majesties most illustrious chappell ; ingrauen by William Hole |
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Pubbl/distr/stampa |
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England, : For Mris. Dor. Euans ..., are to be sould by G. Lowe printer in Southberry |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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2. |
Record Nr. |
UNINA9910483938503321 |
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Titolo |
Deep Learning Classifiers with Memristive Networks : Theory and Applications / / edited by Alex Pappachen James |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
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ISBN |
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Edizione |
[1st ed. 2020.] |
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Descrizione fisica |
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1 online resource (216 pages) |
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Collana |
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Modeling and Optimization in Science and Technologies, , 2196-7326 ; ; 14 |
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Disciplina |
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Soggetti |
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Computational intelligence |
Pattern perception |
Data mining |
Optical data processing |
Computational Intelligence |
Pattern Recognition |
Data Mining and Knowledge Discovery |
Image Processing and Computer Vision |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references. |
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Sommario/riassunto |
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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. |
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