Name: On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling (Springer Theses, 4) (en Inglés)
SKU: 62114454
Price: 114.57 USD
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Author: Addisson Salazar
ISBN: 9783642428753

portada On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling (Springer Theses, 4) (en Inglés)

On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling (Springer Theses, 4) (en Inglés)

Formato

Libro Físico

Editorial

Springer

Autor

Addisson Salazar

Idioma

Inglés

N° páginas

208

Encuadernación

Tapa Blanda

ISBN13

9783642428753

N° edición

2013th

On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling (Springer Theses, 4) (en Inglés)

Addisson Salazar (Autor) · Springer · Tapa Blanda

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Reseña del libro "On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling (Springer Theses, 4) (en Inglés)"

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.