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Tensor-Based Dynamical Systems de Can Chen

Tensor-Based Dynamical Systems: Synthesis Lectures on Mathematics & Statistics

Autor Can Chen
en Limba Engleză Paperback – 2 apr 2025
This book provides a comprehensive review on tensor algebra, including tensor products, tensor unfolding, tensor eigenvalues, and tensor decompositions.
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Paperback (1) 44371 lei  39-44 zile
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Hardback (1) 48218 lei  39-44 zile
  Springer International Publishing – 5 mar 2024 48218 lei  39-44 zile

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Specificații

ISBN-13: 9783031545078
ISBN-10: 3031545079
Pagini: 124
Dimensiuni: 168 x 240 x 8 mm
Greutate: 0.22 kg
Editura: Springer
Seria Synthesis Lectures on Mathematics & Statistics

Cuprins

Tensors and Tensor Algebra.- Tucker Product Representation.- Einstein Product Representation.- CP/tensor Train Decomposition Representation.- Tensor Vector Product Representation.- Contract Product Representation.- T-product Representation.

Notă biografică

Can Chen, Ph.D. is an Assistant Professor in the School of Data Science and Society with a second appointment in the Department of Mathematics at the University of North Carolina at Chapel Hill. He received the B.S. degree in Mathematics from the University of California, Irvine in 2016, and the M.S. degree in Electrical and Computer Engineering and the Ph.D. degree in Applied and Interdisciplinary Mathematics from the University of Michigan in 2020 and 2021, respectively. He was a Postdoctoral Research Fellow in the Channing Division of Network Medicine at Brigham and Women's Hospital and Harvard Medical School from 2021 to 2023. His research interests span a diverse range of fields, including control theory, network science, tensor algebra, numerical analysis, data science, machine learning, deep learning, hypergraph learning, data analysis, and computational biology.

Textul de pe ultima copertă

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.

Caracteristici

Offers a comprehensive review on tensor algebra Introduces tensor-based dynamical systems and explores the role of tensor algebra in these systems Provides real-world interdisciplinary applications from biology, engineering, and physics