Isbn: 9781138112681 - subspace learning of neural networks: 42 (15 risultati)

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Condizione: New.

Paperback. Condizione: new. Paperback. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Condizione: New. pp. 256.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Paperback / softback. Condizione: New. New copy - Usually dispatched within 4 working days.

Condizione: New. 2017. 1st Edition. paperback. . . . . .

Paperback. Condizione: Brand New. 248 pages. 9.21x6.14x0.63 inches. In Stock.

Condizione: New. 2017. 1st Edition. paperback. . . . . . Books ship from the US and Ireland.

Condizione: New. 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.

Paperback. Condizione: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Paperback. Condizione: new. Paperback. 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Condizione: New. Print on Demand pp. 256.

Condizione: New. PRINT ON DEMAND pp. 256.