Tensor Based Dynamical Systems
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Tensor Based Dynamical Systems
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Author : Can Chen
language : en
Publisher: Springer Nature
Release Date : 2024-03-04
Tensor Based Dynamical Systems written by Can Chen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-04 with Science categories.
This book provides a comprehensive review on tensor algebra, including tensor products, tensor unfolding, tensor eigenvalues, and tensor decompositions. Tensors are multidimensional arrays generalized from vectors and matrices, which can capture higher-order interactions within multiway data. In addition, tensors have wide applications in many domains such as signal processing, machine learning, and data analysis, and the author explores the role of tensors/tensor algebra in tensor-based dynamical systems where system evolutions are captured through various tensor products. The author provides an overview of existing literature on the topic and aims to inspire readers to learn, develop, and apply the framework of tensor-based dynamical systems.
Manifolds Tensor Analysis And Applications
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Author : Ralph Abraham
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Manifolds Tensor Analysis And Applications written by Ralph Abraham 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.
The purpose of this book is to provide core material in nonlinear analysis for mathematicians, physicists, engineers, and mathematical biologists. The main goal is to provide a working knowledge of manifolds, dynamical systems, tensors, and differential forms. Some applications to Hamiltonian mechanics, fluid me chanics, electromagnetism, plasma dynamics and control thcory arc given in Chapter 8, using both invariant and index notation. The current edition of the book does not deal with Riemannian geometry in much detail, and it does not treat Lie groups, principal bundles, or Morse theory. Some of this is planned for a subsequent edition. Meanwhile, the authors will make available to interested readers supplementary chapters on Lie Groups and Differential Topology and invite comments on the book's contents and development. Throughout the text supplementary topics are given, marked with the symbols ~ and {l:;J. This device enables the reader to skip various topics without disturbing the main flow of the text. Some of these provide additional background material intended for completeness, to minimize the necessity of consulting too many outside references. We treat finite and infinite-dimensional manifolds simultaneously. This is partly for efficiency of exposition. Without advanced applications, using manifolds of mappings, the study of infinite-dimensional manifolds can be hard to motivate.
Tensors For Data Processing
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Author : Yipeng Liu
language : en
Publisher: Academic Press
Release Date : 2021-10-21
Tensors For Data Processing written by Yipeng Liu and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-21 with Technology & Engineering categories.
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
Dynamic Network Representation Based On Latent Factorization Of Tensors
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Author : Hao Wu
language : en
Publisher: Springer Nature
Release Date : 2023-03-07
Dynamic Network Representation Based On Latent Factorization Of Tensors written by Hao Wu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-07 with Computers categories.
A dynamic network is frequently encountered in various real industrial applications, such as the Internet of Things. It is composed of numerous nodes and large-scale dynamic real-time interactions among them, where each node indicates a specified entity, each directed link indicates a real-time interaction, and the strength of an interaction can be quantified as the weight of a link. As the involved nodes increase drastically, it becomes impossible to observe their full interactions at each time slot, making a resultant dynamic network High Dimensional and Incomplete (HDI). An HDI dynamic network with directed and weighted links, despite its HDI nature, contains rich knowledge regarding involved nodes’ various behavior patterns. Therefore, it is essential to study how to build efficient and effective representation learning models for acquiring useful knowledge. In this book, we first model a dynamic network into an HDI tensor and present the basic latent factorization of tensors (LFT) model. Then, we propose four representative LFT-based network representation methods. The first method integrates the short-time bias, long-time bias and preprocessing bias to precisely represent the volatility of network data. The second method utilizes a proportion-al-integral-derivative controller to construct an adjusted instance error to achieve a higher convergence rate. The third method considers the non-negativity of fluctuating network data by constraining latent features to be non-negative and incorporating the extended linear bias. The fourth method adopts an alternating direction method of multipliers framework to build a learning model for implementing representation to dynamic networks with high preciseness and efficiency.
The Koopman Operator In Systems And Control
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Author : Alexandre Mauroy
language : en
Publisher: Springer Nature
Release Date : 2020-02-22
The Koopman Operator In Systems And Control written by Alexandre Mauroy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-22 with Technology & Engineering categories.
This book provides a broad overview of state-of-the-art research at the intersection of the Koopman operator theory and control theory. It also reviews novel theoretical results obtained and efficient numerical methods developed within the framework of Koopman operator theory. The contributions discuss the latest findings and techniques in several areas of control theory, including model predictive control, optimal control, observer design, systems identification and structural analysis of controlled systems, addressing both theoretical and numerical aspects and presenting open research directions, as well as detailed numerical schemes and data-driven methods. Each contribution addresses a specific problem. After a brief introduction of the Koopman operator framework, including basic notions and definitions, the book explores numerical methods, such as the dynamic mode decomposition (DMD) algorithm and Arnoldi-based methods, which are used to represent the operator in a finite-dimensional basis and to compute its spectral properties from data. The main body of the book is divided into three parts: theoretical results and numerical techniques for observer design, synthesis analysis, stability analysis, parameter estimation, and identification; data-driven techniques based on DMD, which extract the spectral properties of the Koopman operator from data for the structural analysis of controlled systems; and Koopman operator techniques with specific applications in systems and control, which range from heat transfer analysis to robot control. A useful reference resource on the Koopman operator theory for control theorists and practitioners, the book is also of interest to graduate students, researchers, and engineers looking for an introduction to a novel and comprehensive approach to systems and control, from pure theory to data-driven methods.
From Algebraic Structures To Tensors
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Author : Gérard Favier
language : en
Publisher: John Wiley & Sons
Release Date : 2020-01-02
From Algebraic Structures To Tensors written by Gérard Favier and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-02 with Technology & Engineering categories.
Nowadays, tensors play a central role for the representation, mining, analysis, and fusion of multidimensional, multimodal, and heterogeneous big data in numerous fields. This set on Matrices and Tensors in Signal Processing aims at giving a self-contained and comprehensive presentation of various concepts and methods, starting from fundamental algebraic structures to advanced tensor-based applications, including recently developed tensor models and efficient algorithms for dimensionality reduction and parameter estimation. Although its title suggests an orientation towards signal processing, the results presented in this set will also be of use to readers interested in other disciplines. This first book provides an introduction to matrices and tensors of higher-order based on the structures of vector space and tensor space. Some standard algebraic structures are first described, with a focus on the hilbertian approach for signal representation, and function approximation based on Fourier series and orthogonal polynomial series. Matrices and hypermatrices associated with linear, bilinear and multilinear maps are more particularly studied. Some basic results are presented for block matrices. The notions of decomposition, rank, eigenvalue, singular value, and unfolding of a tensor are introduced, by emphasizing similarities and differences between matrices and tensors of higher-order.
Data Driven Science And Engineering
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Author : Steven L. Brunton
language : en
Publisher: Cambridge University Press
Release Date : 2022-05-05
Data Driven Science And Engineering written by Steven L. Brunton and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-05 with Computers categories.
A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.
Data Driven Identification Of Networks Of Dynamic Systems
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Author : Michel Verhaegen
language : en
Publisher: Cambridge University Press
Release Date : 2022-05-12
Data Driven Identification Of Networks Of Dynamic Systems written by Michel Verhaegen and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-12 with Mathematics categories.
A comprehensive introduction to identifying network-connected systems, covering models and methods, and applications in adaptive optics.
Social Robotics
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Author : Shuzhi Sam Ge
language : en
Publisher: Springer
Release Date : 2018-11-26
Social Robotics written by Shuzhi Sam Ge and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-26 with Computers categories.
This book constitutes the refereed proceedings of the 10th International Conference on Social Robotics, ICSR 2018, held in Qingdao, China, in November 2018.The 60 full papers presented were carefully reviewed and selected from 79 submissions. The theme of the 2018 conference is: Social Robotics and AI. In addition to the technical sessions, ICSR 2018 included 2 workshops:Smart Sensing Systems: Towards Safe Navigation and Social Human-Robot Interaction of Service Robots.
Research Anthology On Ecosystem Conservation And Preserving Biodiversity
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Author : Management Association, Information Resources
language : en
Publisher: IGI Global
Release Date : 2022-04-08
Research Anthology On Ecosystem Conservation And Preserving Biodiversity written by Management Association, Information Resources and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-08 with Science categories.
In today’s rapidly evolving world, it has never been more critical to consider key environmental issues such as climate change, pollution, and endangered species. Society faces an unknown future where the fate of the environment is continuously in flux based on current preservation initiatives that governments develop. In order to ensure the world is protected moving forward, further study on the importance of securing environments, ecosystems, and species is necessary to successfully implement change. The Research Anthology on Ecosystem Conservation and Preserving Biodiversity considers the best practices and strategies for protecting our current ecosystems as well as the potential ramifications of failing to implement policies. Society is at a crossroads where if we continue to ignore the danger and warning signs brought about by environmental issues, we will be unable to maintain a healthy environment. Covering essential topics such as extinction, climate change, and pollution, this major reference work is ideal for scientists, industry professionals, researchers, academicians, policymakers, scholars, practitioners, instructors, and students.