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Overview of Tensor Methods for Multi-dimensional Signals Change Detection and Compression

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Image Processing and Communications (IP&C 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1062))

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Abstract

An overview of modern tensor based methods for multi-dimensional signal processing is presented. Special focus is laid on recent achievements in signal change detection, as well as on efficient methods of their compression based on various tensor decompositions. Apart from theory, applications as well as implementation issues are presented as well.

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Acknowledgments

This work was supported by the National Science Centre, Poland, under the grant NCN no. 2016/21/B/ST6/01461.

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Authors and Affiliations

  1. AGH University of Science and Technology, Al. Mickiewicza 30, 30-059, Kraków, Poland

    Bogusław Cyganek

Authors
  1. Bogusław Cyganek
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Correspondence to Bogusław Cyganek .

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Editors and Affiliations

  1. Institute of Telecommunications and Computer Science, University of Science and Technology (UTP), Bydgoszcz, Poland

    Michał Choraś

  2. Department of Telecommunications, Computer Sciences and Electrical Engineering, University of Science and Technology (UTP), Bydgoszcz, Poland

    Ryszard S. Choraś

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Cyganek, B. (2020). Overview of Tensor Methods for Multi-dimensional Signals Change Detection and Compression. In: Choraś, M., Choraś, R. (eds) Image Processing and Communications. IP&C 2019. Advances in Intelligent Systems and Computing, vol 1062. Springer, Cham. https://doi.org/10.1007/978-3-030-31254-1_1

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