Download Advanced Intelligent Computing Theories and Applications. by Lvzhou Li, Daowen Qiu (auth.), De-Shuang Huang, Xiang Zhang, PDF

By Lvzhou Li, Daowen Qiu (auth.), De-Shuang Huang, Xiang Zhang, Carlos Alberto Reyes García, Lei Zhang (eds.)

The overseas convention on clever Computing (ICIC) used to be shaped to supply an annual discussion board devoted to the rising and not easy themes in man made intel- gence, computing device studying, trend acceptance, snapshot processing, bioinformatics, and computational biology. It goals to compile researchers and practitioners from either academia and to proportion rules, difficulties, and options concerning the m- tifaceted points of clever computing. ICIC 2010, held in Changsha, China, August 18–21, 2010, constituted the sixth - ternational convention on clever Computing. It outfitted upon the luck of ICIC 2009, ICIC 2008, ICIC 2007, ICIC 2006, and ICIC 2005, that have been held in Ulsan, Korea, Shanghai, Qingdao, Kunming, and Hefei, China, respectively. This yr, the convention focused customarily at the theories and methodologies in addition to the rising functions of clever computing. Its goal was once to unify the image of latest clever computing suggestions as an indispensable idea that highlights the traits in complicated computational intelligence and bridges theoretical learn with purposes. accordingly, the subject for this convention was once “Advanced clever Computing know-how and Applications.” Papers targeting this topic have been solicited, addressing theories, methodologies, and functions in technology and technology.

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Extra info for Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence: 6th International Conference on Intelligent Computing, ICIC 2010, Changsha, China, August 18-21, 2010. Proceedings

Sample text

Consider a gene expression dataset that consists of p genes in n samples. We denote it by a matrix X with size p × n . Without loss of generality, we assume that the column and row means of X are zero. The singular value decomposition (SVD) of the data matrix X can be written as follows: X = UDV T , U T U = I p , V T V = I n (1) The PMD generalizes this decomposition by imposing additional constraints on U and V. t. u 2 2 1 X − duvT 2 = 1, v 2 2 2 F (2) = 1, P1 (u) ≤ α1 , P2 ( v) ≤ α 2 , d ≥ 0.

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Local analytic solutions of a functional differential equation with a deviating argument depending on the state derivative near resonance. Comput. Math. Appl. 54, 750–762 (2007) 10. : Analytic form of differential equations. Trans. Moscow Math. Soc.. 25, 131–288 (1971) 11. : The Brjuno functions and their regularity properties. Comm. Math. Phys.. 186(2), 265–293 (1997) 12. : Linearization of Analytic and Non-Analytic Germs of Diffeomorphisms of (C, O). Bull. Soc. Math. France. 128, 69–85 (2000) 13.

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