Subspace Learning of Neural Networks: 42 - Brossura

Cheng Lv, Jian; Yi, Zhang; Zhou, Jiliu

Brossura

ISBN 10: 1138112682 ISBN 13: 9781138112681

Casa editrice: CRC Press, 2017

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.

Su questo libro

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.

Dettagli dell'edizione

• Editore: CRC Press
• Data di pubblicazione: 2017
• Lingua: Inglese
• ISBN 10: 1138112682
• ISBN 13: 9781138112681
• Rilegatura: Copertina flessibile
• Numero edizione: 1
• Numero di pagine: 256
• Contatto del produttore: Taylor and Francis, GPSR Taylor and Francis; gpsr@taylorandfrancis.com; ; Taylor & Francis Verlag GmbH, Kaufingerstraße 24; München; 80331; Germania