Hyperchaotic Bilateral Random Low-Rank Approximation Random Sequence Generation Method and Its Application on Compressive Ghost Imaging

Songyuan Tan, Jingru Sun, Yiping Tang, Yichuang Sun, Chunhua Wang

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Abstract

Hyperchaotic systems have been widely used in the field of communication and information security to generate random numbers due to their super-long sequences, pseudo-randomness, and unpredictability. However, chaotic systems still have certain periodicity and security risks. To improve the reliability of chaotic random sequences, in this paper, a new method of generating chaotic random sequences based on random bilateral projection is proposed. Through random bilateral projection algorithm, the matrix formed by chaotic sequences is decomposed into a noiseless low-rank matrix, sparse matrix, and noise matrix, and the noise matrix is retained as a random sequence, which can effectively remove the regular factors to improve the randomness of the generated sequence. To verify the effectiveness of the proposed sequence generation method, we apply it to the compressive ghost imaging encryption system, and through simulation verified that compared with the existing algorithms, the proposed random sequence generation method has better efficiency and randomness, and can improve the security and efficiency of the compressive ghost imaging system.
Original languageEnglish
JournalNonlinear Dynamics
DOIs
Publication statusPublished - 15 Feb 2024

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