On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling

Language: English

Published by Springer, 2014

3642428754 / 9783642428753

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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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Druck auf Anfrage Neuware - Printed after ordering - 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.

Seller Inventory # 9783642428753

Title
On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling
Author
Addisson Salazar
Publisher
Springer
Publication year
2014
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
3642428754
ISBN 13
9783642428753
Item weight
324 grams
Dimensions
235x155x12 mm

AHA-BUCH GmbH

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