A Memristive Hyperjerk Chaotic System: Amplitude Control, FPGA Design, and Prediction with Artificial Neural Network

Wang, Ran; Li, Chunbiao; Çiçek, Serdar; Rajagopal, Karthikeyan; Zhang, Xin

doi:10.1155/2021/6636813

Cited by 14 publications

(10 citation statements)

References 45 publications

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“…e system ( 1) is stabilized by using controllers (17), adaptation rules (18), and compensators (19).…”

Section: Theoremmentioning

confidence: 99%

“…Stabilization. In this section, the dynamics of ( 1) is stabilized by controller (17), tuning rules (18), and compensator (19). e simulation conditions are described in Table 1.…”

Section: Simulationmentioning

confidence: 99%

“…For chaotic systems, some neurofuzzy methods have also been studied. For example, in [17], NNs are used for prediction problems in Hyperjerk CSs and their physical circuit implementation is investigated. e finite-time synchronization of CSs is studied in [18] and, by analyzing the convergence time, an FLS-based controller is presented.…”

Section: Introductionmentioning

confidence: 99%

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A Type-3 Fuzzy Approach for Stabilization and Synchronization of Chaotic Systems: Applicable for Financial and Physical Chaotic Systems

et al. 2022

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In this paper, a new approach is presented for stabilizing and synchronizing financial chaotic systems. A new type-3 (T3) fuzzy-based system (FLS) with an online optimization scheme is designed to cope with chaotic behavior, high-level uncertainties, and unknown dynamics. An adaptive compensator also eliminates the effect of approximation errors (AEs) and perturbations. The stability of the dynamics of synchronization errors is guaranteed by the use of the Lyapunov method. Several simulations and comparisons demonstrate the superiority of the suggested control and synchronization scenarios.

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“…e system ( 1) is stabilized by using controllers (17), adaptation rules (18), and compensators (19).…”

Section: Theoremmentioning

confidence: 99%

“…Stabilization. In this section, the dynamics of ( 1) is stabilized by controller (17), tuning rules (18), and compensator (19). e simulation conditions are described in Table 1.…”

Section: Simulationmentioning

confidence: 99%

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A Type-3 Fuzzy Approach for Stabilization and Synchronization of Chaotic Systems: Applicable for Financial and Physical Chaotic Systems

et al. 2022

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“…So far, the system designed in this way has high program readability, high logic synthesis efficiency, and good program portability. Without phase truncation, the output phase sequence of the phase accumulator Y½n is as follows [5,6]:…”

Section: Electromagnetic Occlusion Algorithmmentioning

confidence: 99%

Electromagnetic Occlusion Algorithm Based on FPGA and Panel Grouping and Its Optimization

Cao

2021

Wireless Communications and Mobile Computing

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With the development of digital signal processing and advanced algorithms, real-time signal processing based on FPGA and DSP is suitable for high-speed radar signal processing. With the rapid development of science and technology, war has entered the information age guided by high technology, and advanced science and technology has played a vital role in the trend of war. In recent years in the modern war, many countries invest a lot of research effort on the stealth technology, and advanced stealth technology can use a variety of technical means to alter or weaken the feature information of the target, confuse the enemy radar detection system effectively, reduce the chance of being detected to the largest extent, and prolong the lifecycle of aircraft and weapons. This research mainly discusses the electromagnetic occlusion algorithm and its optimization based on FPGA and panel grouping. The FPGA model selected for this study is XC6VLX240T-1FF1156I. Because the amount of data processed here is not very large, the cache part directly uses the on-chip storage resources of the FPGA, and the AD device is used to perform analog-to-digital/digital-to-analog conversion on the signal and perform digital up-down conversion. For a facet, it is necessary to first verify whether it is a bright facet and set the flag to mark it, then the facet needs to be occluded with the triangular facet marked as a bright facet, and all bright facets that have been marked need to be traversed. Open MP parallelization of the occlusion algorithm is as follows: The physical optics method is used to calculate the target RCS, and the focus of parallelism is placed on the part with a large amount of calculation. When using Open MP to design a program on a multicore computer, each group is assigned a thread to give full play to the core computing power. The total field is scattered and superimposed by each surface element. This part uses the parallel processing mode of Open MP, which allows the panel judgment in the group to be carried out at the same time. This part requires schedule to allocate resources and use different parallel mechanisms for different calculations to optimize debugging. In the angular range where there is multiple scattering at 0 ° ≤ φ ≤ 90 ° , the calculation results and the measurement results are in good agreement, and when the two planes are simulated with 1820 triangular faces, the fast multiple scattering in this paper only needs 4 minutes. This research has realized the general radar signal processing method based on FPGA structure, and the design has important engineering realization significance.

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“…Therefore, the design of memristor chaotic circuits using FPGA is significant for practical applications. Nowadays, a variety of memristor chaotic systems have been implemented by FPGA [34,[40][41][42][43]-for instance, FPGA realization of a novel 5D hyperchaotic fourwing memristive system [44], FPGA implementation of a memristor-based multi-scroll hyperchaotic system [45], etc.…”

Section: Introductionmentioning

confidence: 99%

Implementation of the Simple Hyperchaotic Memristor Circuit with Attractor Evolution and Large-Scale Parameter Permission

Yang

Zhang

Moshayedi

2023

Entropy

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A novel, simple, four-dimensional hyperchaotic memristor circuit consisting of two capacitors, an inductor and a magnetically controlled memristor is designed. Three parameters (a, b, c) are especially set as the research objects of the model through numerical simulation. It is found that the circuit not only exhibits a rich attractor evolution phenomenon, but also has large-scale parameter permission. At the same time, the spectral entropy complexity of the circuit is analyzed, and it is confirmed that the circuit contains a significant amount of dynamical behavior. By setting the internal parameters of the circuit to remain constant, a number of coexisting attractors are found under symmetric initial conditions. Then, the results of the attractor basin further confirm the coexisting attractor behavior and multiple stability. Finally, the simple memristor chaotic circuit is designed by the time-domain method with FPGA technology and the experimental results have the same phase trajectory as the numerical calculation results. Hyperchaos and broad parameter selection mean that the simple memristor model has more complex dynamic behavior, which can be widely used in the future, in areas such as secure communication, intelligent control and memory storage.

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A Memristive Hyperjerk Chaotic System: Amplitude Control, FPGA Design, and Prediction with Artificial Neural Network

Cited by 14 publications

References 45 publications

A Type-3 Fuzzy Approach for Stabilization and Synchronization of Chaotic Systems: Applicable for Financial and Physical Chaotic Systems

A Type-3 Fuzzy Approach for Stabilization and Synchronization of Chaotic Systems: Applicable for Financial and Physical Chaotic Systems

Electromagnetic Occlusion Algorithm Based on FPGA and Panel Grouping and Its Optimization

Implementation of the Simple Hyperchaotic Memristor Circuit with Attractor Evolution and Large-Scale Parameter Permission

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