Download Blind Source Separation: Theory and Applications by Xianchuan Yu PDF

By Xianchuan Yu

A systematic exploration of either vintage and modern algorithms in blind resource separation with sensible case studies   

The e-book provides an summary of Blind resource Separation, a comparatively new sign processing method.  as a result of multidisciplinary nature of the topic, the ebook has been written with the intention to entice an viewers from very various backgrounds. simple mathematical talents (e.g. on matrix algebra and foundations of likelihood conception) are crucial that allows you to comprehend the algorithms, even if the ebook is written in an introductory, obtainable style.

This ebook deals a common assessment of the fundamentals of Blind resource Separation, vital ideas and algorithms, and in-depth insurance of purposes in picture characteristic extraction, distant sensing photograph fusion, mixed-pixel decomposition of SAR pictures, snapshot item acceptance fMRI clinical photograph processing, geochemical and geophysical facts mining, mineral assets prediction and geoanomalies info popularity. to begin with, the historical past and idea fundamentals of blind resource separation are brought, which gives the basis for the subsequent paintings. Matrix operation, foundations of likelihood idea and data conception fundamentals are integrated right here. There follows the elemental mathematical version and reasonably new yet particularly confirmed blind resource separation algorithms, equivalent to self reliant part research (ICA) and its better algorithms (Fast ICA, greatest chance ICA, Overcomplete ICA, Kernel ICA, versatile ICA, Non-negative ICA, limited ICA, Optimised ICA). The final a part of the publication considers the very fresh algorithms in BSS e.g. Sparse part research (SCA) and Non-negative Matrix Factorization (NMF). in the meantime, in-depth situations are awarded for every set of rules on the way to aid the reader comprehend the set of rules and its program field.

  • A systematic exploration of either vintage and modern algorithms in blind resource separation with sensible case studies
  • Presents new more desirable algorithms geared toward various functions, equivalent to photograph function extraction, distant sensing snapshot fusion, mixed-pixel decomposition of SAR pictures, picture item popularity, and MRI clinical snapshot processing
  • With functions in geochemical and geophysical info mining, mineral assets prediction and geoanomalies info recognition
  • Written via a professional crew with authorised concepts in blind resource separation and its functions in ordinary science
  • Accompanying site contains a software program procedure supplying codes for many of the algorithms pointed out within the booklet, bettering the training experience

Essential analyzing for postgraduate scholars and researchers engaged within the zone of sign processing, facts mining, picture processing and popularity, info, geosciences, existence sciences.

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Additional info for Blind Source Separation: Theory and Applications

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1991) Face recognition using eigenfaces. Proceedings of IEEE Conferences on Computer Vision and Pattern Recognition, Maui, HI, pp. 586–591. , and Karhunen, J. (2002) An unsupervised ensemble learning method for nonlinear dynamic state-space models. Neural Computation, 14(11), 2647–2692. Vincent, E. (2005) Musical source separation using time-frequency source priors. IEEE Transactions on Speech and Audio Processing, 14(1), 91–98. Y. (1997) Blind source separation of instantaneous mixtures. Acta Electronica Sinica, 25(4), 1–5 (in Chinese).

Part I Basic Theory of BSS 2 Mathematical Foundation of Blind Source Separation Some readers may be interested in the mathematical background behind the various blind source separation techniques. In this chapter, we review key concepts and formulas that are essential for this purpose, including matrix analysis, higher-order statistics, and information theory. Readers who have a good knowledge of these concepts can skip most of this chapter. 1 Determinant and Its Properties 1. 2) where t is the reverse number of the row mark.

Chapter 2 introduces a basic knowledge of mathematics, including matrix operations, probability theory, Introduction 11 and information theory. Then, the basic mathematical models and classic algorithms for BSS are presented in Chapter 3. Chapter 4 focuses on the definition of the BSS algorithm evaluation criteria. More confident readers may prefer to skip some or all of the introductory chapters in Part 1 and continue directly to the principles of BSS in Part 2. Part II (Chapters 5–14) covers the core algorithm for BSS, namely, ICA.

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