Enhanced hardware implementation of a mixed-order nonlinear chaotic system and speech encryption application

Author(s):  
Abdulaziz H. Elsafty ◽  
Mohammed F. Tolba ◽  
Lobna A. Said ◽  
Ahmed H. Madian ◽  
Ahmed G. Radwan
Author(s):  
Balamurali Ramakrishnan ◽  
Atefeh Ahmadi ◽  
Fahimeh Nazarimehr ◽  
Hayder Natiq ◽  
Sajad Jafari ◽  
...  

2011 ◽  
Vol 383-390 ◽  
pp. 6992-6997 ◽  
Author(s):  
Ai Xue Qi ◽  
Cheng Liang Zhang ◽  
Guang Yi Wang

This paper presents a method that utilizes a memristor to replace the non-linear resistance of typical Chua’s circuit for constructing a chaotic system. The improved circuit is numerically simulated in the MATLAB condition, and its hardware implementation is designed using field programmable gate array (FPGA). Comparing the experimental results with the numerical simulation, the two are the very same, and be able to generate chaotic attractor.


Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-8 ◽  
Author(s):  
Peng An ◽  
Wen-Feng Wang ◽  
Xi Chen ◽  
Jing Qian ◽  
Yunzhu Pan

Chaos theory has been proved to be of great significance in a series of critical applications although, until now, its applications in analyzing soil respiration have not been addressed. This study aims to introduce a chaotic component in the control system of soil respiration and explain control complexity of this nonlinear chaotic system. This also presents a theoretical framework for better understanding chaotic components of soil respiration in arid land. A concept model of processes and mechanisms associated with subterranean CO2 evolution are developed, and dynamics of the chaotic system is characterized as an extended Riccati equation. Controls of soil respiration and kinetics of the chaotic system are interpreted and as a first attempt, control complexity of this nonlinear chaotic system is tackled by introducing a period-regulator in partitioning components of soil respiration.


2020 ◽  
Vol 14 ◽  
pp. 174830262092250
Author(s):  
Yan Li ◽  
Yigang He ◽  
Wenxin Yu

The study of nonlinear chaotic systems and their control is an important topic. In this paper, a hybrid control strategy based on cuckoo search algorithm and extreme learning machine is proposed. Cuckoo search algorithm is used in a hybrid control strategy in order to optimise the weights and biases in extreme learning machine leading to the improvement of its performance. Simulations indicate that the proposed method is able to fit nonlinear chaotic systems and control chaotic systems effectively. Data used in the nonlinear chaotic system are also tested for uncertainty and unknown systems. Simulation results confirm that the proposed method shows robustness for noisy data and perturbed parameters.


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