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Adaptive Synchronization-Based Approach for Finite-Time Parameters Identification of Genetic Regulatory Networks

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Abstract

This paper presents an approach to identify the unknown parameters of genetic regulatory network (GRN) in finite-time. The adaptive synchronization-based method is used to solve this problem. Specifically, an auxiliary system with adaptive parameters is constructed, which is regarded as slave system of the GRN with unknown parameters. Then, effective update laws of adaptive parameters and variable structure controllers are designed. The criteria of synchronization and parameters identification in finite-time are derived by utilizing finite-time Lyapunov stability theorem. Finally, an illustrative example is given to show the effectiveness of the main results.

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Authors and Affiliations

  1. School of Mathematical Sciences, Qufu Normal University, Qufu, 273165, Shandong, People’s Republic of China

    Fei Wang & Zhaowen Zheng

  2. Laboratory of Mathematics and Complex Systems (Ministry of Education of China), School of Mathematical Sciences, Beijing Normal University, Beijing, 100875, People’s Republic of China

    Yuru Li

Authors
  1. Yuru Li
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  2. Fei Wang
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  3. Zhaowen Zheng
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Correspondence to Fei Wang.

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This work was jointly supported by the Project funded by the China Postdoctoral Science Foundation No. 2020M672027, the Natural Science Foundation of Shandong Province of China under Grant No. ZR2019MA034, the Youth Creative Team Sci-Tech Program of Shandong Universities (Grant no. 2019KJI007), the National Natural Science Foundation of China under Grant 61973183.

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Li, Y., Wang, F. & Zheng, Z. Adaptive Synchronization-Based Approach for Finite-Time Parameters Identification of Genetic Regulatory Networks. Neural Process Lett 54, 3141–3156 (2022). https://doi.org/10.1007/s11063-022-10754-4

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