Titlebook: Independent Component Analysis; Theory and Applicati Te-Won Lee Book 1998 Springer-Verlag US 1998 Independent Component Analysis.algorithms

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Te-Won Leeess, low density, and so on. This attractive package is marred by one deadly flaw, namely, an utter lack of toughness. They are prone to catastrophic failures in the presence of flaws (surface or internal). They are extremely susceptible to thermal shock and are easily damaged during fabrication and

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ce. The first edition of .Composite Materials. introduced a new way of looking at composite materials: covering composites in accordance with their functions. This second edition expands the book’s scope to emphasize application-driven and process-oriented materials development. Although application

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Basicsocessing. The material presented here was selected from several textbooks. The goal of this chapter is to cover the basic notions and terminologies used throughout the thesis. It is not intended to give a broad understanding of the theories but rather to recall some definitions and their relations t

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Unsupervised Classification with ICA Mixture Modelsh the observed data can be categorized into several data classes. The data in each class is generated by a linear mixture of independent sources and is called an ICA class. The goal of the learning algorithm is first to find the independent sources and the mixing matrix for each ICA class and second