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Review

Research Status of Nonlinear Feedback Shift Register Based on Semi-Tensor Product

School of Mathematics, Shandong University, Jinan 250100, China
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Mathematics 2022, 10(19), 3538; https://doi.org/10.3390/math10193538
Submission received: 3 September 2022 / Revised: 21 September 2022 / Accepted: 26 September 2022 / Published: 28 September 2022
(This article belongs to the Section E: Applied Mathematics)

Abstract

Nonlinear feedback shift registers (NFSRs) are the main components of stream ciphers and convolutional decoders. Recent years have seen an increase in the requirement for information security, which has sparked NFSR research. However, the NFSR study is very imperfect as a result of the lack of appropriate mathematical tools. Many scholars have discovered in recent years that the introduction of semi-tensor products (STP) of matrices can overcome this issue because STP can convert the NFSR into a quasi-linear form. As a result of STP, new NFSR research has emerged from a different angle. In view of this, in order to generalize the latest achievements of NFSRs based on STP and provide some directions for future development, the research results are summarized and sorted out, broadly including the modeling of NFSRs, the analysis of the structure of NFSRs, and the study of the properties of NFSRs.
Keywords: semi-tensor product; nonlinear feedback shift register; equivalence; nonsingularity; stability semi-tensor product; nonlinear feedback shift register; equivalence; nonsingularity; stability

Share and Cite

MDPI and ACS Style

Gao, Z.; Feng, J.-e. Research Status of Nonlinear Feedback Shift Register Based on Semi-Tensor Product. Mathematics 2022, 10, 3538. https://doi.org/10.3390/math10193538

AMA Style

Gao Z, Feng J-e. Research Status of Nonlinear Feedback Shift Register Based on Semi-Tensor Product. Mathematics. 2022; 10(19):3538. https://doi.org/10.3390/math10193538

Chicago/Turabian Style

Gao, Zhe, and Jun-e Feng. 2022. "Research Status of Nonlinear Feedback Shift Register Based on Semi-Tensor Product" Mathematics 10, no. 19: 3538. https://doi.org/10.3390/math10193538

APA Style

Gao, Z., & Feng, J.-e. (2022). Research Status of Nonlinear Feedback Shift Register Based on Semi-Tensor Product. Mathematics, 10(19), 3538. https://doi.org/10.3390/math10193538

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