On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling (Record no. 51652)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 03076nam a22005295i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-3-642-30752-2 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20200420220217.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 120720s2013 gw | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9783642307522 |
| -- | 978-3-642-30752-2 |
| 082 04 - CLASSIFICATION NUMBER | |
| Call Number | 621.382 |
| 100 1# - AUTHOR NAME | |
| Author | Salazar, Addisson. |
| 245 10 - TITLE STATEMENT | |
| Title | On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | XXII, 186 p. |
| 490 1# - SERIES STATEMENT | |
| Series statement | Springer Theses, Recognizing Outstanding Ph.D. Research, |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Remark 2 | Introduction -- ICA and ICAMM Methods -- Learning Mixtures of Independent Component Analysers -- Hierarchical Clustering from ICA Mixtures -- Application of ICAMM to Impact-Echo Testing -- Cultural Heritage Applications: Archaeological Ceramics and Building Restoration -- Other Applications: Sequential Dependence Modelling and Data Mining -- Conclusions. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | 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. |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | http://dx.doi.org/10.1007/978-3-642-30752-2 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 264 #1 - | |
| -- | Berlin, Heidelberg : |
| -- | Springer Berlin Heidelberg : |
| -- | Imprint: Springer, |
| -- | 2013. |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
| -- | c |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
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| 347 ## - | |
| -- | text file |
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| -- | rda |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Engineering. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Pattern recognition. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Complexity, Computational. |
| 650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Engineering. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Signal, Image and Speech Processing. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Pattern Recognition. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Complexity. |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| -- | 2190-5053 ; |
| 912 ## - | |
| -- | ZDB-2-ENG |
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