Tensors for Data Processing

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Publisher : Academic Press
ISBN 13 : 0323859658
Total Pages : 598 pages
Book Rating : 4.3/5 (238 download)

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Book Synopsis Tensors for Data Processing by : Yipeng Liu

Download or read book Tensors for Data Processing written by Yipeng Liu and published by Academic Press. This book was released on 2021-10-21 with total page 598 pages. Available in PDF, EPUB and Kindle. Book excerpt: Tensors for Data Processing: Theory, Methods and Applications presents both classical and state-of-the-art methods on tensor computation for data processing, covering computation theories, processing methods, computing and engineering applications, with an emphasis on techniques for data processing. This reference is ideal for students, researchers and industry developers who want to understand and use tensor-based data processing theories and methods. As a higher-order generalization of a matrix, tensor-based processing can avoid multi-linear data structure loss that occurs in classical matrix-based data processing methods. This move from matrix to tensors is beneficial for many diverse application areas, including signal processing, computer science, acoustics, neuroscience, communication, medical engineering, seismology, psychometric, chemometrics, biometric, quantum physics and quantum chemistry. - Provides a complete reference on classical and state-of-the-art tensor-based methods for data processing - Includes a wide range of applications from different disciplines - Gives guidance for their application

Intelligent Computing Methodologies

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Publisher : Springer
ISBN 13 : 3319959573
Total Pages : 896 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Intelligent Computing Methodologies by : De-Shuang Huang

Download or read book Intelligent Computing Methodologies written by De-Shuang Huang and published by Springer. This book was released on 2018-08-08 with total page 896 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes - in conjunction with the two-volume set LNCS 10954 and LNCS 10955 - the refereed proceedings of the 14th International Conference on Intelligent Computing, ICIC 2018, held in Wuhan, China, in August 2018. The 275 full papers and 72 short papers of the three proceedings volumes were carefully reviewed and selected from 632 submissions. The papers are organized in topical sections such as Evolutionary Computation and Learning; Neural Networks; Pattern Recognition; Image Processing; Information Security; Virtual Reality and Human-Computer Interaction; Business Intelligence and Multimedia Technology; Biomedical Informatics Theory and Methods; Swarm Intelligence and Optimization; Natural Computing; Quantum Computing; Intelligent Computing in Computer Vision; Fuzzy Theory and Algorithms; Machine Learning; Systems Biology; Intelligent Systems and Applications for Bioengineering; Evolutionary Optimization: Foundations and Its Applications to Intelligent Data Analytics; Swarm Evolutionary Algorithms for Scheduling and Combinatorial Optimization; Swarm Intelligence and Applications in Combinatorial Qoptimization; Advances in Metaheuristic Optimization Algorithm; Advances in Image Processing and Pattern Techniques; Bioinformatics.

Handbook of Robust Low-Rank and Sparse Matrix Decomposition

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Publisher : CRC Press
ISBN 13 : 1315353539
Total Pages : 510 pages
Book Rating : 4.3/5 (153 download)

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Book Synopsis Handbook of Robust Low-Rank and Sparse Matrix Decomposition by : Thierry Bouwmans

Download or read book Handbook of Robust Low-Rank and Sparse Matrix Decomposition written by Thierry Bouwmans and published by CRC Press. This book was released on 2016-09-20 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Robust Low-Rank and Sparse Matrix Decomposition: Applications in Image and Video Processing shows you how robust subspace learning and tracking by decomposition into low-rank and sparse matrices provide a suitable framework for computer vision applications. Incorporating both existing and new ideas, the book conveniently gives you one-stop access to a number of different decompositions, algorithms, implementations, and benchmarking techniques. Divided into five parts, the book begins with an overall introduction to robust principal component analysis (PCA) via decomposition into low-rank and sparse matrices. The second part addresses robust matrix factorization/completion problems while the third part focuses on robust online subspace estimation, learning, and tracking. Covering applications in image and video processing, the fourth part discusses image analysis, image denoising, motion saliency detection, video coding, key frame extraction, and hyperspectral video processing. The final part presents resources and applications in background/foreground separation for video surveillance. With contributions from leading teams around the world, this handbook provides a complete overview of the concepts, theories, algorithms, and applications related to robust low-rank and sparse matrix decompositions. It is designed for researchers, developers, and graduate students in computer vision, image and video processing, real-time architecture, machine learning, and data mining.

Mathematical Aspects of Computer and Information Sciences

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Publisher : Springer
ISBN 13 : 3319724533
Total Pages : 466 pages
Book Rating : 4.3/5 (197 download)

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Book Synopsis Mathematical Aspects of Computer and Information Sciences by : Johannes Blömer

Download or read book Mathematical Aspects of Computer and Information Sciences written by Johannes Blömer and published by Springer. This book was released on 2017-12-20 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 7th International Conference on Mathematical Aspects of Computer and Information Sciences, MACIS 2017, held in Vienna, Austria, in November 2017. The 28 revised papers and 8 short papers presented were carefully reviewed and selected from 67 submissions. The papers are organized in the following topical sections: foundation of algorithms in mathematics, engineering and scientific computation; combinatorics and codes in computer science; data modeling and analysis; and mathematical aspects of information security and cryptography.

Data Fusion Methodology and Applications

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Publisher : Elsevier
ISBN 13 : 0444639853
Total Pages : 398 pages
Book Rating : 4.4/5 (446 download)

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Book Synopsis Data Fusion Methodology and Applications by : Marina Cocchi

Download or read book Data Fusion Methodology and Applications written by Marina Cocchi and published by Elsevier. This book was released on 2019-05-11 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Fusion Methodology and Applications explores the data-driven discovery paradigm in science and the need to handle large amounts of diverse data. Drivers of this change include the increased availability and accessibility of hyphenated analytical platforms, imaging techniques, the explosion of omics data, and the development of information technology. As data-driven research deals with an inductive attitude that aims to extract information and build models capable of inferring the underlying phenomena from the data itself, this book explores the challenges and methodologies used to integrate data from multiple sources, analytical platforms, different modalities, and varying timescales. - Presents the first comprehensive textbook on data fusion, focusing on all aspects of data-driven discovery - Includes comprehensible, theoretical chapters written for large and diverse audiences - Provides a wealth of selected application to the topics included

Image and Graphics

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Publisher : Springer Nature
ISBN 13 : 3030873587
Total Pages : 838 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Image and Graphics by : Yuxin Peng

Download or read book Image and Graphics written by Yuxin Peng and published by Springer Nature. This book was released on 2021-09-30 with total page 838 pages. Available in PDF, EPUB and Kindle. Book excerpt: This three-volume set LNCS 12888, 12898, and 12890 constitutes the refereed conference proceedings of the 11th International Conference on Image and Graphics, ICIG 2021, held in Haikou, China, in August 2021.* The 198 full papers presented were selected from 421 submissions and focus on advances of theory, techniques and algorithms as well as innovative technologies of image, video and graphics processing and fostering innovation, entrepreneurship, and networking. *The conference was postponed due to the COVID-19 pandemic.

Tensor Numerical Methods in Scientific Computing

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Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3110391392
Total Pages : 475 pages
Book Rating : 4.1/5 (13 download)

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Book Synopsis Tensor Numerical Methods in Scientific Computing by : Boris N. Khoromskij

Download or read book Tensor Numerical Methods in Scientific Computing written by Boris N. Khoromskij and published by Walter de Gruyter GmbH & Co KG. This book was released on 2018-06-11 with total page 475 pages. Available in PDF, EPUB and Kindle. Book excerpt: The most difficult computational problems nowadays are those of higher dimensions. This research monograph offers an introduction to tensor numerical methods designed for the solution of the multidimensional problems in scientific computing. These methods are based on the rank-structured approximation of multivariate functions and operators by using the appropriate tensor formats. The old and new rank-structured tensor formats are investigated. We discuss in detail the novel quantized tensor approximation method (QTT) which provides function-operator calculus in higher dimensions in logarithmic complexity rendering super-fast convolution, FFT and wavelet transforms. This book suggests the constructive recipes and computational schemes for a number of real life problems described by the multidimensional partial differential equations. We present the theory and algorithms for the sinc-based separable approximation of the analytic radial basis functions including Green’s and Helmholtz kernels. The efficient tensor-based techniques for computational problems in electronic structure calculations and for the grid-based evaluation of long-range interaction potentials in multi-particle systems are considered. We also discuss the QTT numerical approach in many-particle dynamics, tensor techniques for stochastic/parametric PDEs as well as for the solution and homogenization of the elliptic equations with highly-oscillating coefficients. Contents Theory on separable approximation of multivariate functions Multilinear algebra and nonlinear tensor approximation Superfast computations via quantized tensor approximation Tensor approach to multidimensional integrodifferential equations

An Introduction to Structural Mechanics for Architects

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Publisher : Springer
ISBN 13 : 3319729357
Total Pages : 241 pages
Book Rating : 4.3/5 (197 download)

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Book Synopsis An Introduction to Structural Mechanics for Architects by : Elías Cueto

Download or read book An Introduction to Structural Mechanics for Architects written by Elías Cueto and published by Springer. This book was released on 2018-05-23 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook offers an introductory course to structural mechanics for architects, including problems and solutions. It follows a completely different approach to structural mechanics than the usual books for engineering schools, making it much more attractive for architecture students and practitioners. It also offers a different point of view for engineering students, as it provides them with a more intuitive understanding of structural mechanics and the models therein.Instead of studying the classical theory of linear elasticity and then particularizing it to simple structures, this book analyzes structures in a historic and also typological order. The book starts with cable structures and stone arches, followed by trusses and, finally, frame structures made of beams. For every typology, the latest, state-of-the-art theory in the field is introduced in a very didactic way.

Artificial Intelligence Algorithms and Applications

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Publisher : Springer Nature
ISBN 13 : 981155577X
Total Pages : 811 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Artificial Intelligence Algorithms and Applications by : Kangshun Li

Download or read book Artificial Intelligence Algorithms and Applications written by Kangshun Li and published by Springer Nature. This book was released on 2020-05-25 with total page 811 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed proceedings of the 11th International Symposium on Intelligence Computation and Applications, ISICA 2019, held in Guangzhou, China, in November 2019. The 65 papers presented were carefully reviewed and selected from the total of 112 submissions. This volume features the most up-to-date research in evolutionary algorithms, parallel computing and quantum computing, evolutionary multi-objective and dynamic optimization, intelligent multimedia systems, virtualization and AI applications, smart scheduling, intelligent control, big data and cloud computing, deep learning, and hybrid machine learning systems.The papers are organized according to the following topical sections: new frontier in evolutionary algorithms; evolutionary multi-objective and dynamic optimization; intelligent multimedia systems; virtualization and AI applications; smart scheduling; intelligent control; big data and cloud computing; statistical learning.

Tensor Computation for Data Analysis

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Publisher : Springer Nature
ISBN 13 : 3030743861
Total Pages : 347 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Tensor Computation for Data Analysis by : Yipeng Liu

Download or read book Tensor Computation for Data Analysis written by Yipeng Liu and published by Springer Nature. This book was released on 2021-08-31 with total page 347 pages. Available in PDF, EPUB and Kindle. Book excerpt: Tensor is a natural representation for multi-dimensional data, and tensor computation can avoid possible multi-linear data structure loss in classical matrix computation-based data analysis. This book is intended to provide non-specialists an overall understanding of tensor computation and its applications in data analysis, and benefits researchers, engineers, and students with theoretical, computational, technical and experimental details. It presents a systematic and up-to-date overview of tensor decompositions from the engineer's point of view, and comprehensive coverage of tensor computation based data analysis techniques. In addition, some practical examples in machine learning, signal processing, data mining, computer vision, remote sensing, and biomedical engineering are also presented for easy understanding and implementation. These data analysis techniques may be further applied in other applications on neuroscience, communication, psychometrics, chemometrics, biometrics, quantum physics, quantum chemistry, etc. The discussion begins with basic coverage of notations, preliminary operations in tensor computations, main tensor decompositions and their properties. Based on them, a series of tensor-based data analysis techniques are presented as the tensor extensions of their classical matrix counterparts, including tensor dictionary learning, low rank tensor recovery, tensor completion, coupled tensor analysis, robust principal tensor component analysis, tensor regression, logistical tensor regression, support tensor machine, multilinear discriminate analysis, tensor subspace clustering, tensor-based deep learning, tensor graphical model and tensor sketch. The discussion also includes a number of typical applications with experimental results, such as image reconstruction, image enhancement, data fusion, signal recovery, recommendation system, knowledge graph acquisition, traffic flow prediction, link prediction, environmental prediction, weather forecasting, background extraction, human pose estimation, cognitive state classification from fMRI, infrared small target detection, heterogeneous information networks clustering, multi-view image clustering, and deep neural network compression.

Generalized Inverses

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Publisher : Springer Science & Business Media
ISBN 13 : 0387216340
Total Pages : 433 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Generalized Inverses by : Adi Ben-Israel

Download or read book Generalized Inverses written by Adi Ben-Israel and published by Springer Science & Business Media. This book was released on 2006-04-18 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: This second edition accounts for many major developments in generalized inverses while maintaining the informal and leisurely style of the 1974 first edition. Added material includes a chapter on applications, new exercises, and an appendix on the work of E.H. Moore.

Digital TV and Wireless Multimedia Communication

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Publisher : Springer Nature
ISBN 13 : 9811533415
Total Pages : 431 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Digital TV and Wireless Multimedia Communication by : Guangtao Zhai

Download or read book Digital TV and Wireless Multimedia Communication written by Guangtao Zhai and published by Springer Nature. This book was released on 2020-02-15 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents revised selected papers from the 16th International Forum on Digital TV and Wireless Multimedia Communication, IFTC 2019, held in Shanghai, China, in September 2019. The 34 full papers presented in this volume were carefully reviewed and selected from 120 submissions. They were organized in topical sections on image processing; machine learning; quality assessment; telecommunications; video surveillance; virtual reality.

Multimodal and Tensor Data Analytics for Industrial Systems Improvement

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Publisher : Springer Nature
ISBN 13 : 3031530926
Total Pages : 388 pages
Book Rating : 4.0/5 (315 download)

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Book Synopsis Multimodal and Tensor Data Analytics for Industrial Systems Improvement by : Nathan Gaw

Download or read book Multimodal and Tensor Data Analytics for Industrial Systems Improvement written by Nathan Gaw and published by Springer Nature. This book was released on with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Knowledge Science, Engineering and Management

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Publisher : Springer Nature
ISBN 13 : 303110983X
Total Pages : 780 pages
Book Rating : 4.0/5 (311 download)

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Book Synopsis Knowledge Science, Engineering and Management by : Gerard Memmi

Download or read book Knowledge Science, Engineering and Management written by Gerard Memmi and published by Springer Nature. This book was released on 2022-07-19 with total page 780 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume sets constitute the refereed proceedings of the 15th International Conference on Knowledge Science, Engineering and Management, KSEM 2022, held in Singapore, during August 6–8, 2022. The 169 full papers presented in these proceedings were carefully reviewed and selected from 498 submissions. The papers are organized in the following topical sections: Volume I: Knowledge Science with Learning and AI (KSLA) Volume II: Knowledge Engineering Research and Applications (KERA) Volume III: Knowledge Management with Optimization and Security (KMOS)

Structured Matrices in Mathematics, Computer Science, and Engineering I

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Publisher : American Mathematical Soc.
ISBN 13 : 0821819216
Total Pages : 346 pages
Book Rating : 4.8/5 (218 download)

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Book Synopsis Structured Matrices in Mathematics, Computer Science, and Engineering I by : Vadim Olshevsky

Download or read book Structured Matrices in Mathematics, Computer Science, and Engineering I written by Vadim Olshevsky and published by American Mathematical Soc.. This book was released on 2001 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The collection of the contributions to these volumes offers a flavor of the plethora of different approaches to attack structured matrix problems. The reader will find that the theory of structured matrices is positioned to bridge diverse applications in the sciences and engineering, deep mathematical theories, as well as computational and numberical issues. The presentation fully illustrates the fact that the technicques of engineers, mathematicisn, and numerical analysts nicely complement each other, and they all contribute to one unified theory of structured matrices"--Back cover.

Nonnegative Matrix and Tensor Factorizations

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Publisher : John Wiley & Sons
ISBN 13 : 9780470747285
Total Pages : 500 pages
Book Rating : 4.7/5 (472 download)

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Book Synopsis Nonnegative Matrix and Tensor Factorizations by : Andrzej Cichocki

Download or read book Nonnegative Matrix and Tensor Factorizations written by Andrzej Cichocki and published by John Wiley & Sons. This book was released on 2009-07-10 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a broad survey of models and efficient algorithms for Nonnegative Matrix Factorization (NMF). This includes NMF’s various extensions and modifications, especially Nonnegative Tensor Factorizations (NTF) and Nonnegative Tucker Decompositions (NTD). NMF/NTF and their extensions are increasingly used as tools in signal and image processing, and data analysis, having garnered interest due to their capability to provide new insights and relevant information about the complex latent relationships in experimental data sets. It is suggested that NMF can provide meaningful components with physical interpretations; for example, in bioinformatics, NMF and its extensions have been successfully applied to gene expression, sequence analysis, the functional characterization of genes, clustering and text mining. As such, the authors focus on the algorithms that are most useful in practice, looking at the fastest, most robust, and suitable for large-scale models. Key features: Acts as a single source reference guide to NMF, collating information that is widely dispersed in current literature, including the authors’ own recently developed techniques in the subject area. Uses generalized cost functions such as Bregman, Alpha and Beta divergences, to present practical implementations of several types of robust algorithms, in particular Multiplicative, Alternating Least Squares, Projected Gradient and Quasi Newton algorithms. Provides a comparative analysis of the different methods in order to identify approximation error and complexity. Includes pseudo codes and optimized MATLAB source codes for almost all algorithms presented in the book. The increasing interest in nonnegative matrix and tensor factorizations, as well as decompositions and sparse representation of data, will ensure that this book is essential reading for engineers, scientists, researchers, industry practitioners and graduate students across signal and image processing; neuroscience; data mining and data analysis; computer science; bioinformatics; speech processing; biomedical engineering; and multimedia.

Pattern Recognition and Computer Vision

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Publisher : Springer Nature
ISBN 13 : 9819784875
Total Pages : 581 pages
Book Rating : 4.8/5 (197 download)

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Book Synopsis Pattern Recognition and Computer Vision by : Zhouchen Lin

Download or read book Pattern Recognition and Computer Vision written by Zhouchen Lin and published by Springer Nature. This book was released on with total page 581 pages. Available in PDF, EPUB and Kindle. Book excerpt: