On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling

Language: English

Published by Springer, Springer Jul 2012, 2012

3642307515 / 9783642307515

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This item is printed on demand - Print on Demand Titel. Neuware -A natural evolution of statistical signal processing, in connection with the progressive increase in computational power, has been exploiting higher-order information. Thus, high-order spectral analysis and nonlinear adaptive filtering have received the attention of many researchers. One of the most successful techniques for non-linear processing of data with complex non-Gaussian distributions is the independent component analysis mixture modelling (ICAMM). This thesis defines a novel formalism for pattern recognition and classification based on ICAMM, which unifies a certain number of pattern recognition tasks allowing generalization. The versatile and powerful framework developed in this work can deal with data obtained from quite different areas, such as image processing, impact-echo testing, cultural heritage, hypnograms analysis, web-mining and might therefore be employed to solve many different real-world problems.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 208 pp. Englisch.…

Seller Inventory # 9783642307515

Title
On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling
Author
Addisson Salazar
Publisher
Springer, Springer Jul 2012
Publication year
2012
Condition
Neu
Binding
Buch
Language
English
ISBN 10
3642307515
ISBN 13
9783642307515
Item weight
483 grams
Dimensions
241x160x16 mm

buchversandmimpf2000

Emtmannsberg, BAYE, Germany

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