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Subspace Learning of Neural Networks by Zhang Yi, Jian Cheng Lv, Jiliu Zhou (Hardback, 2010)
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item 2 - Subspace Learning of Neural Networks, Jian Cheng Lv
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About this product
Description
- DescriptionUsing 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.
- Author BiographyJian 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.
Key Features
- Author(s)Jian Cheng Lv,Jiliu Zhou,Zhang Yi
- PublisherTaylor & Francis Inc
- Date of Publication21/09/2010
- LanguageEnglish
- FormatHardback
- ISBN-101439815356
- ISBN-139781439815359
- SubjectElectronics Engineering & Communications Engineering
- Series TitleAutomation and Control Engineering
- Series Part/Volume Numberv. 42
Publication Data
- Place of PublicationBosa Roca
- Country of PublicationUnited States
- ImprintCRC Press Inc
- Content Note84 black & white illustrations, 5 black & white tables
Dimensions
- Weight498 g
- Width156 mm
- Height235 mm
- Spine18 mm
Editorial Details
- Format DetailsUnsewn / adhesive bound
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