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DCT-Net: A Neurodynamic Approach with Definable Convergence Property for Real-Time Synchronization of Chaotic Systems
Dechao Chen 
,
Shuai Li
,
Shuai Li
Neural Processing Letters, Volume: 55, Issue: 1, Pages: 819 - 837
Swansea University Author:
Shuai Li
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DOI (Published version): 10.1007/s11063-022-10911-9
Abstract
Because of complexity during real-time synchronization of chaotic systems in practical applications, the convergence process with a definable-time (or to say, finite-time) property is urgently needed. To amend convergent property during real-time synchronization of chaotic system, this paper propose...
| Published in: | Neural Processing Letters |
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| ISSN: | 1370-4621 1573-773X |
| Published: |
Springer Science and Business Media LLC
2023
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| Online Access: |
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa60254 |
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| Abstract: |
Because of complexity during real-time synchronization of chaotic systems in practical applications, the convergence process with a definable-time (or to say, finite-time) property is urgently needed. To amend convergent property during real-time synchronization of chaotic system, this paper proposes a novel definable-convergence-time (DCT) neurodynamic approach for designing the associated neural network, called DCT-Net. Quite differing from the conventional zeroing neurodynamic (CZN) approach showing undefinable convergent time, the DCT-Net distinctively illustrates superiority of DCT property making synchronization of chaotic system faster and higher precision. In addition, theorems about globally stable in addition to convergent property are rigorously proved in detail. Moreover, different simulative examples substantiate the validity of DCT-Net for real-time synchronization of chaotic system. Comprehensive comparisons with other existing nets further verify advantages. At last, different tests detailedly discover the influence on convergent property by selecting various user-defined parameters as well as initial state. |
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| Keywords: |
Zeroing neurodynamic approach; Definable convergence time; Real-time synchronization; DCT-Net; Chaotic systems |
| College: |
Faculty of Science and Engineering |
| Funders: |
This work is supported by the National Natural Science Foundation of China (with number 61906054), by Zhejiang Provincial Natural Science Foundation of China (with number LY21-F030006). |
| Issue: |
1 |
| Start Page: |
819 |
| End Page: |
837 |