Synchronization of analog and discrete Rössler chaotic systems

Butusov, Denis N.; Каримов, Тимур; Lizunova, Inna; Soldatkina, Alina A.; Попова, Е. Н.

doi:10.1109/eiconrus.2017.7910544

Cited by 17 publications

(12 citation statements)

References 7 publications

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“…The synchronization of electronic circuits is found in [17][18][19][20]. The synchronization of digital and analog chaotic systems was discussed in [21][22]. We recently proposed a new disturbance observer based on D-stability for synchronizing two nonidentical T-S fuzzy chaotic systems.…”

Section: Introductionmentioning

confidence: 99%

Synthetic Adaptive Fuzzy Disturbance Observer and Sliding-Mode Control for Chaos-Based Secure Communication Systems

2021

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Section: Introductionmentioning

confidence: 99%

Synthetic Adaptive Fuzzy Disturbance Observer and Sliding-Mode Control for Chaos-Based Secure Communication Systems

2021

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“…In a previous work, a practical possibility for the synchronization between analog and digital chaotic systems was shown experimentally [14]. This result leads to an idea that one of the possible ways to verify digital chaotic models is the synchronization between these models and their continuous counterparts.…”

Section: Introductionmentioning

confidence: 75%

“…The phase portraits of the corresponding synchronization errors are presented in Figure 7. Figure 7a demonstrates the data obtained in the literature [14]. Figure 7b shows the result of synchronization after the identification procedure.…”

Section: Digital-analog Chaotic Oscillators Synchronizationmentioning

confidence: 99%

Accurate Synchronization of Digital and Analog Chaotic Systems by Parameters Re-Identification

et al. 2018

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The verification of the digital models of chaotic systems and processes is a valuable problem in many practical applications, such as nonlinear control and communications. In our study, we propose a hybrid technique for chaotic systems' identification, based on the chaotic synchronization of digital and analog counterparts and a numerical optimization method used for the fine tuning of parameters. An analog circuit implementing the Rössler oscillator with digitally controlled parameters was chosen as an identification object, and the FPGA model was used as a digital counterpart for coupling and parameter retrieval. The synchronization between analog and digital chaotic models can be used to estimate the quality of an identification procedure. The results of this study clarify the practical bounds of digital and analog systems' equivalence. They also contribute to the problem of designing technical systems possessing advantages of both analog and digital chaotic generators (e.g., a high accuracy and protection from quasi-chaotic oscillation modes).

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“…It allows the construction of computationally cheap symmetric methods, and it is easy to construct parallel algorithms [27]. Recently it has been discussed for the solution of various chaotic systems [28]- [30].…”

Section: Implementation Of the Proposed Methodsmentioning

confidence: 99%

“…Besides, the system can be realized simply either by independent circuit structure [28] as shown in [31] or by recursive algorithm with universal digital integrated circuit.…”

Section: Implementation Of the Proposed Methodsmentioning

confidence: 99%

Signal Denoising Based on Duffing Oscillators System

Luo¹,

Cui

2020

IEEE Access

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Signal denoising is an important aspect of signal processing. It is a meaningful direction to solve this problem by using chaotic oscillator. As a kind of chaotic oscillator, Duffing oscillator is often used in the field of periodic signal or pulse signal detection, but it has not been used in signal denoising. In this paper, a new Duffing oscillators system for signal denoising is proposed. The system utilizes the coupling between linear and nonlinear restoring forces of the oscillators to achieve complete synchronization of the system. Because the external signal will cause a large deviation of the oscillator's trajectory, while the Gauss white noise will only produce a small deviation. Based on this phenomenon, signal denoising can be realized. The simulation results show that, compared with the existing technology, our method is effective for the denoising of complex irregular signal, and can recover the mutation points of signal well. This method has less computational complexity and is easy to implement parallel computation. It can be used in real-time signal processing.

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Synchronization of analog and discrete Rössler chaotic systems

Cited by 17 publications

References 7 publications

Synthetic Adaptive Fuzzy Disturbance Observer and Sliding-Mode Control for Chaos-Based Secure Communication Systems

Synthetic Adaptive Fuzzy Disturbance Observer and Sliding-Mode Control for Chaos-Based Secure Communication Systems

Accurate Synchronization of Digital and Analog Chaotic Systems by Parameters Re-Identification

Signal Denoising Based on Duffing Oscillators System

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