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  • Language: English

    Published by Springer, 2014

    3642428754 / 9783642428753

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  • Language: English

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  • Language: English

    Published by Springer, 2012

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  • Language: English

    Published by Springer, 2012

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  • Language: English

    Published by Springer, 2014

    3642428754 / 9783642428753

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    Condition: New. pp. 208.

  • Language: English

    Published by Springer, 2012

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  • Language: English

    Published by Springer, 2012

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    Buch. Condition: Neu. 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.…

  • Language: English

    Published by Springer, 2014

    3642428754 / 9783642428753

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    Taschenbuch. Condition: Neu. 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.…

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    Language: English

    Published by Springer, 2014

    3642428754 / 9783642428753

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    Taschenbuch. Condition: Neu. On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling | Addisson Salazar | Taschenbuch | Springer Theses | xxii | Englisch | 2014 | Springer | EAN 9783642428753 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

  • Language: English

    Published by Springer Verlag, 2012

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    Hardcover. Condition: Brand New. 2013 edition. 207 pages. 9.65x0.71x6.46 inches. In Stock.

  • Language: English

    Published by Springer, 2012

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  • Language: English

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  • Language: English

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  • Language: English

    Published by Springer, 2014

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  • Language: English

    Published by Springer, 2014

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  • Language: English

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  • Language: English

    Published by Springer, 2014

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  • Language: English

    Published by Springer 2014-08, 2014

    3642428754 / 9783642428753

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    PF. Condition: New. This item is printed on demand. Brand new book, sourced directly from publisher. Dispatch time is 6-7 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

  • Language: English

    Published by Springer Berlin Heidelberg Jul 2012, 2012

    3642307515 / 9783642307515

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    Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - 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. 208 pp. Englisch.…

  • Language: English

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    Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - 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. 208 pp. Englisch.…

  • Language: English

    Published by Springer Berlin Heidelberg, 2014

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    Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Nominated as an outstanding PhD theses by the Polytechnic University of ValenciaPresent an excellent state-of-the-art literature review of the main applied theoretical foundations of statistical pattern recognition Gives new insights into.…

  • Language: English

    Published by Springer Berlin Heidelberg, 2012

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    Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Nominated as an outstanding PhD theses by the Polytechnic University of ValenciaPresent an excellent state-of-the-art literature review of the main applied theoretical foundations of statistical pattern recognition Gives new insights into.…

  • Language: English

    Published by Springer, Springer Jul 2012, 2012

    3642307515 / 9783642307515

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    Buch. Condition: Neu. 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.…

  • Language: English

    Published by Springer, Springer Aug 2014, 2014

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    Taschenbuch. Condition: Neu. 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 GmbH, Tiergartenstr. 17, 69121 Heidelberg 208 pp. Englisch.…

  • Language: English

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    Condition: New. Print on Demand pp. 208 73 Figures, 49:B&W 6.14 x 9.21 in or 234 x 156 mm (Royal 8vo) Perfect Bound on White w/Gloss Lam.

  • Language: English

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    Condition: New. Print on Demand pp. 208 73 Figures, 52:B&W 6.14 x 9.21in or 234 x 156mm (Royal 8vo) Case Laminate on White w/Gloss Lam.

  • Language: English

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    Condition: New. PRINT ON DEMAND pp. 208.

  • Language: English

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    Condition: New. PRINT ON DEMAND pp. 208.