Subspace Learning of Neural Networks

Cheng, Jian/ Yi, Zhang/ Zhou, Jiliu

ISBN 10: 1138112682 / ISBN 13: 9781138112681

Editore: CRC Pr I Llc, 2017

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248 pages. 9.21x6.14x0.63 inches. In Stock.

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Dati bibliografici

• Titolo: Subspace Learning of Neural Networks
• Editore: CRC Pr I Llc
• Data di pubblicazione: 2017
• Lingua: Inglese
• ISBN 10: 1138112682
• ISBN 13: 9781138112681
• Rilegatura: Paperback
• Condizione: Brand New
• Peso: 0,47 chilogrammi

Descrizione articolo

Riassunto

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.

Informazioni sull?autore

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.