In 1901, Karl Pearson invented Principal Component Analysis (PCA). Since then, PCA serves as a prototype for many other tools of data analysis, visualization and dimension reduction: Independent Component Analysis (IC...
ISBN:
(数字)9783540737506
ISBN:
(纸本)9783540737490
In 1901, Karl Pearson invented Principal Component Analysis (PCA). Since then, PCA serves as a prototype for many other tools of data analysis, visualization and dimension reduction: Independent Component Analysis (ICA), Multidimensional Scaling (MDS), Nonlinear PCA (NLPCA), Self Organizing Maps (SOM), etc. The book starts with the quote of the classical Pearson definition of PCA and includes reviews of various methods: NLPCA, ICA, MDS, embedding and clustering algorithms, principal manifolds and SOM. New approaches to NLPCA, principal manifolds, branching principal components and topology preserving mappings are described as well. Presentation of algorithms is supplemented by case studies, from engineering to astronomy, but mostly of biological data: analysis of microarray and metabolite data. The volume ends with a tutorial "PCA and K-means decipher genome". The book is meant to be useful for practitioners in applied data analysis in life sciences, engineering, physics and chemistry; it will also be valuable to PhD students and researchers in computer sciences, applied mathematics and statistics.
Modeling and computations in electromagnetics is a quite novel and growing discipline, expanding as a result of the steadily increasing demand for designing electrical devices, modeling electromagnetic materials, and ...
ISBN:
(数字)9783540737780
ISBN:
(纸本)9783540737773
Modeling and computations in electromagnetics is a quite novel and growing discipline, expanding as a result of the steadily increasing demand for designing electrical devices, modeling electromagnetic materials, and simulating electromagnetic fields in nanoscale structures. The aim of this volume is to bring together prominent worldwide experts to review state-of-the-art developments and future trends of modeling and computations in electromagnetics. This volume is devoted to merging the expertise of scientists working in this dynamic discipline, and to raising interest for challenging issues. The most significant advances in computational techniques have been made only in the last few years, and several challenging technological applications are presented in this volume.
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