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Matrix Methods in Data Mining and Pattern Recognition
Several very powerful numerical linear algebra techniques are available for solving problems in data mining and pattern recognition. This application-oriented book describes how modern matrix methods can be used to solve these problems, gives an introduction to matrix theory and decompositions, and provides students with a set of tools that can be modified for a particular application.Matrix Methods in Data Mining and Pattern Recognition is divided into three parts. Part I gives a short introduction to a few application areas before presenting linear algebra concepts and matrix decompositions that students can use in problem-solving environments such as MATLAB®. Some mathematical proofs tha...
Materials Science Research in Japan
Compilation of various summaries, overviews and reports on recent advances in high-technology science research in Japan.
Basket Three, Implementation of the Helsinki Accords: Soviet Helsinki watch, reports on repression. U.S. policy and the Belgrade Conference
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Basket Three, Implementation of the Helsinki Accords: Soviet Helsinki watch, reports on represiion. U.S. policy and the Belgrade Congerence
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Matrix Algorithms
This volume is the first in a self-contained five-volume series devoted to matrix algorithms. It focuses on the computation of matrix decompositions--that is, the factorization of matrices into products of similar ones. The first two chapters provide the required background from mathematics and computer science needed to work effectively in matrix computations. The remaining chapters are devoted to the LU and QR decompositions--their computation and applications. The singular value decomposition is also treated, although algorithms for its computation will appear in the second volume of the series. The present volume contains 65 algorithms formally presented in pseudocode. Other volumes in t...
Recent Advances in Computational Sciences
This book presents state-of-the-art lectures delivered by international academic and industrial experts in the field of computational science and its education, covering a wide spectrum from theory to practice. Topics include new developments in finite element method (FEM), finite volume method and Spline theory, such as Moving Mesh Methods, Galerkin and Discontinuous Galerkin Schemes, Shape Gradient Methods, Mixed FEMs, Superconvergence techniques and Fourier spectral approximations with applications in multidimensional fluid dynamics; Maxwell equations in discrepancy media; and phase-field equations. It also discusses some interesting topics related to Stokes equations, Schrodinger equations, wavelet analysis and approximation theory. Contemporary teaching issues in curriculum reform also form an integral part of the book. This book will therefore be of significant interest and value to all graduates, research scientists and practitioners facing complex computational problems. Administrators and policymakers will find it is an addition to their mathematics curriculum reform libraries.
Intelligent Science and Intelligent Data Engineering
This book constitutes the proceedings of the Sino-foreign-interchange Workshop on Intelligence Science and Intelligent Data Engineering, IScIDE 2011, held in Xi'an, China, in October 2011. The 97 papers presented were carefully peer-reviewed and selected from 389 submissions. The IScIDE papers in this volume are organized in topical sections on machine learning and computational intelligence; pattern recognition; computer vision and image processing; graphics and computer visualization; knowledge discovering, data mining, web mining; multimedia processing and application.
