| 书目名称 | On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling |
| 编辑 | Addisson Salazar |
| 视频video | |
| 概述 | Nominated as an outstanding PhD theses by the Polytechnic University of Valencia.Present an excellent state-of-the-art literature review of the main applied theoretical foundations of statistical patt |
| 丛书名称 | Springer Theses |
| 图书封面 |  |
| 描述 | 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. |
| 出版日期 | Book 2013 |
| 关键词 | Classification of Archaeological Ceramics; Image Processing; Impact-echo Measurements; Independent Comp |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-642-30752-2 |
| isbn_softcover | 978-3-642-42875-3 |
| isbn_ebook | 978-3-642-30752-2Series ISSN 2190-5053 Series E-ISSN 2190-5061 |
| issn_series | 2190-5053 |
| copyright | Springer-Verlag Berlin Heidelberg 2013 |
发表于 2025-3-21 18:28:09
