Sparsity And Its Applications
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Sparsity And Its Applications
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Author : David J. Evans
language : en
Publisher: CUP Archive
Release Date : 1985-01-10
Sparsity And Its Applications written by David J. Evans and has been published by CUP Archive this book supported file pdf, txt, epub, kindle and other format this book has been release on 1985-01-10 with Mathematics categories.
Good,No Highlights,No Markup,all pages are intact, Slight Shelfwear,may have the corners slightly dented, may have slight color changes/slightly damaged spine.
Sparse Coding And Its Applications In Computer Vision
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Author : Zhaowen E. T. Al WANG
language : en
Publisher: World Scientific
Release Date : 2015-10-28
Sparse Coding And Its Applications In Computer Vision written by Zhaowen E. T. Al WANG and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-28 with Computers categories.
"This book provides a broader introduction to the theories and applications of sparse coding techniques in computer vision research. It introduces sparse coding in the context of representation learning, illustrates the fundamental concepts, and summarizes the most active research directions. A variety of applications of sparse coding are discussed, ranging from low-level image processing tasks such as super-resolution and de-blurring to high-level semantic understanding tasks such as image recognition, clustering and fusion. The book is suitable to be used as an introductory overview to this field, with its theoretical part being both easy and precious enough for quick understanding. It is also of great value to experienced researchers as it offers new perspective to the underlying mechanism of sparse coding, and points out potential future directions for different applications."--
Sparsity
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Author : A. Brameller
language : en
Publisher: Pitman Publishing
Release Date : 1976
Sparsity written by A. Brameller and has been published by Pitman Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 1976 with Mathematics categories.
Sparsity Measures And Their Signal Processing Applications For Machine Condition Monitoring
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Author : Dong Wang
language : en
Publisher: Elsevier
Release Date : 2025-02-01
Sparsity Measures And Their Signal Processing Applications For Machine Condition Monitoring written by Dong Wang and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-01 with Technology & Engineering categories.
Sparsity Measures and their Signal Processing Applications for Machine Condition Monitoring presents newly designed sparsity measures and their advanced signal processing technologies for machine condition monitoring and fault diagnosis. This book systematically covers new sparsity measures including a quasiarithmetic mean ratio framework for fault signatures quantification, a generalized Gini index, as well as classic sparsity measures based on signal processing technologies and a cycle-embedded sparsity measure based on new impulsive mode decomposition technology. This book additionally includes a sparsity measure data-driven framework–based optimized weights spectrum theory and its relevant advanced signal processing technologies. - Provides the background, roadmaps and detailed discussion of newly designed sparsity measures and their advanced signal processing technologies for machine condition monitoring and fault diagnosis - Covers new theories, advanced technologies, and the latest contributions in the field of machine condition monitoring and fault diagnosis - Particularly focuses on newly advanced sparsity measures for fault signature quantification, classic and advanced sparsity measures–based signal processing technologies and sparsity measures using data-driven framework–based signal processing technologies - Provides experimental and real-world practical validation cases, including newly advanced sparsity measures and their advanced signal processing technologies
Computational Methods For General Sparse Matrices
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Author : Zahari Zlatev
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-04-17
Computational Methods For General Sparse Matrices written by Zahari Zlatev and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-17 with Mathematics categories.
Compressed Sensing And Its Applications
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Author : Holger Boche
language : en
Publisher: Birkhäuser
Release Date : 2019-08-13
Compressed Sensing And Its Applications written by Holger Boche and has been published by Birkhäuser this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-13 with Mathematics categories.
The chapters in this volume highlight the state-of-the-art of compressed sensing and are based on talks given at the third international MATHEON conference on the same topic, held from December 4-8, 2017 at the Technical University in Berlin. In addition to methods in compressed sensing, chapters provide insights into cutting edge applications of deep learning in data science, highlighting the overlapping ideas and methods that connect the fields of compressed sensing and deep learning. Specific topics covered include: Quantized compressed sensing Classification Machine learning Oracle inequalities Non-convex optimization Image reconstruction Statistical learning theory This volume will be a valuable resource for graduate students and researchers in the areas of mathematics, computer science, and engineering, as well as other applied scientists exploring potential applications of compressed sensing.
Graph Theory And Sparse Matrix Computation
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Author : Alan George
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Graph Theory And Sparse Matrix Computation written by Alan George and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.
When reality is modeled by computation, matrices are often the connection between the continuous physical world and the finite algorithmic one. Usually, the more detailed the model, the bigger the matrix, the better the answer, however, efficiency demands that every possible advantage be exploited. The articles in this volume are based on recent research on sparse matrix computations. This volume looks at graph theory as it connects to linear algebra, parallel computing, data structures, geometry, and both numerical and discrete algorithms. The articles are grouped into three general categories: graph models of symmetric matrices and factorizations, graph models of algorithms on nonsymmetric matrices, and parallel sparse matrix algorithms. This book will be a resource for the researcher or advanced student of either graphs or sparse matrices; it will be useful to mathematicians, numerical analysts and theoretical computer scientists alike.
Sparse Representation Modeling And Learning In Visual Recognition
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Author : Hong Cheng
language : en
Publisher: Springer
Release Date : 2015-05-25
Sparse Representation Modeling And Learning In Visual Recognition written by Hong Cheng and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-05-25 with Computers categories.
This unique text/reference presents a comprehensive review of the state of the art in sparse representations, modeling and learning. The book examines both the theoretical foundations and details of algorithm implementation, highlighting the practical application of compressed sensing research in visual recognition and computer vision. Topics and features: describes sparse recovery approaches, robust and efficient sparse representation, and large-scale visual recognition; covers feature representation and learning, sparsity induced similarity, and sparse representation and learning-based classifiers; discusses low-rank matrix approximation, graphical models in compressed sensing, collaborative representation-based classification, and high-dimensional nonlinear learning; includes appendices outlining additional computer programming resources, and explaining the essential mathematics required to understand the book.
Practical Applications Of Sparse Modeling
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Author : Irina Rish
language : en
Publisher: MIT Press
Release Date : 2014-09-12
Practical Applications Of Sparse Modeling written by Irina Rish and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-12 with Computers categories.
"Sparse modeling is a rapidly developing area at the intersection of statistical learning and signal processing, motivated by the age-old statistical problem of selecting a small number of predictive variables in high-dimensional data sets. This collection describes key approaches in sparse modeling, focusing on its applications in such fields as neuroscience, computational biology, and computer vision. Sparse modeling methods can improve the interpretability of predictive models and aid efficient recovery of high-dimensional unobserved signals from a limited number of measurements. Yet despite significant advances in the field, a number of open issues remain when sparse modeling meets real-life applications. The book discusses a range of practical applications and state-of-the-art approaches for tackling the challenges presented by these applications. Topics considered include the choice of method in genomics applications; analysis of protein mass-spectrometry data; the stability of sparse models in brain imaging applications; sequential testing approaches; algorithmic aspects of sparse recovery; and learning sparse latent models"--Jacket.
Sparse Solutions Of Underdetermined Linear Systems And Their Applications
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Author : Ming-Jun Lai
language : en
Publisher: SIAM
Release Date : 2021-06-25
Sparse Solutions Of Underdetermined Linear Systems And Their Applications written by Ming-Jun Lai and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-25 with Mathematics categories.
This textbook presents a special solution to underdetermined linear systems where the number of nonzero entries in the solution is very small compared to the total number of entries. This is called a sparse solution. Since underdetermined linear systems can be very different, the authors explain how to compute a sparse solution using many approaches. Sparse Solutions of Underdetermined Linear Systems and Their Applications contains 64 algorithms for finding sparse solutions of underdetermined linear systems and their applications for matrix completion, graph clustering, and phase retrieval and provides a detailed explanation of these algorithms including derivations and convergence analysis. Exercises for each chapter help readers understand the material. This textbook is appropriate for graduate students in math and applied math, computer science, statistics, data science, and engineering. Advisors and postdoctoral scholars will also find the book interesting and useful.