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Synopsis
Using real-life examples to illustrate the performance of learning algorithms and instructing readers how to apply them to practical applications, this work offers a comprehensive treatment of subspace learning algorithms for neural networks. The authors summarize a decade of high quality research offering a host of practical applications. They demonstrate ways to extend the use of algorithms to fields such as encryption communication, data mining, computer vision, and signal and image processing to name just a few. The brilliance of the work lies with how it coherently builds a theoretical understanding of the convergence behavior of subspace learning algorithms through a summary of chaotic behaviors.
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About the Author
Jian Cheng LV and Zhang Yi are affiliated with the Machine Intelligence Lab of the College of Computer Science at Sichuan University. Jiliu Zhou is affiliated with the College of Computer Science at Sichuan University.
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Subspace Learning of Neural Networks
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CRC Press LLC, 2010
ISBN 10: 1439815356
ISBN 13: 9781439815359
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Subspace Learning of Neural Networks
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Subspace Learning of Neural Networks
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Subspace Learning of Neural Networks
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Subspace Learning of Neural Networks
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Subspace Learning of Neural Networks
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Subspace Learning of Neural Networks
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Lv, J: Subspace Learning of Neural Networks
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Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Jian Cheng LV and Zhang Yi are affiliated with the Machine Intelligence Lab of the College of Computer Science at Sichuan University. Jiliu Zhou is affiliated with the College of Computer Science at Sichuan University.Using real-life examp. Seller Inventory # 595834367
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Subspace Learning of Neural Networks
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Subspace Learning of Neural Networks
Published by
Taylor & Francis Inc Sep 2010, 2010
ISBN 10: 1439815356
ISBN 13: 9781439815359
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Buch. Condition: Neu. Neuware - 'Using real-life examples to illustrate the performance of learning algorithms and instructing readers how to apply them to practical applications, this work offers a comprehensive treatment of subspace learning algorithms for neural networks. The authors summarize a decade of high quality research offering a host of practical applications. They demonstrate ways to extend the use of algorithms to fields such as encryption communication, data mining, computer vision, and signal and image processing to name just a few. The brilliance of the work lies with how it coherently builds a theoretical understanding of the convergence behavior of subspace learning algorithms through a summary of chaotic behaviors'--. Seller Inventory # 9781439815359
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