Open AccessBook
Matrix Analysis and Applied Linear Algebra
TLDR
The author presents Perron-Frobenius theory of nonnegative matrices Index, a theory of matrices that combines linear equations, vector spaces, and matrix algebra with insights into eigenvalues and Eigenvectors.Abstract:
Preface 1. Linear equations 2. Rectangular systems and echelon forms 3. Matrix algebra 4. Vector spaces 5. Norms, inner products, and orthogonality 6. Determinants 7. Eigenvalues and Eigenvectors 8. Perron-Frobenius theory of nonnegative matrices Index.read more
Citations
More filters
Book
Kernel Methods for Pattern Analysis
TL;DR: This book provides an easy introduction for students and researchers to the growing field of kernel-based pattern analysis, demonstrating with examples how to handcraft an algorithm or a kernel for a new specific application, and covering all the necessary conceptual and mathematical tools to do so.
Journal ArticleDOI
Finding community structure in networks using the eigenvectors of matrices
TL;DR: A modularity matrix plays a role in community detection similar to that played by the graph Laplacian in graph partitioning calculations, and a spectral measure of bipartite structure in networks and a centrality measure that identifies vertices that occupy central positions within the communities to which they belong are proposed.
Book
Computer Vision: Algorithms and Applications
TL;DR: Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images and takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene.
Journal ArticleDOI
Tracking Whole-Brain Connectivity Dynamics in the Resting State
Elena A. Allen,Eswar Damaraju,Sergey M. Plis,Erik B. Erhardt,Tom Eichele,Vince D. Calhoun,Vince D. Calhoun +6 more
TL;DR: In this article, the authors describe an approach to assess whole-brain functional connectivity dynamics based on spatial independent component analysis, sliding time window correlation, and k-means clustering of windowed correlation matrices.
Book
Parameter estimation and inverse problems
TL;DR: "Parameter Estimation and Inverse Problems, 2/e" introduces readers to both Classical and Bayesian approaches to linear and nonlinear problems with particular attention paid to computational, mathematical, and statistical issues related to their application to geophysical problems.