UID:
almahu_9949744358702882
Format:
XV, 106 p. 19 illus., 17 illus. in color.
,
online resource.
Edition:
1st ed. 2024.
ISBN:
9783031545054
Series Statement:
Synthesis Lectures on Mathematics & Statistics,
Content:
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.
Note:
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.
In:
Springer Nature eBook
Additional Edition:
Printed edition: ISBN 9783031545047
Additional Edition:
Printed edition: ISBN 9783031545061
Additional Edition:
Printed edition: ISBN 9783031545078
Language:
English
DOI:
10.1007/978-3-031-54505-4
URL:
https://doi.org/10.1007/978-3-031-54505-4
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