FPGA Implementation of a Real-Time Weak Signal Detector Using a Duffing Oscillator

Rashtchi, Vahid; Nourazar, Mohsen

doi:10.1007/s00034-014-9948-5

Cited by 45 publications

(20 citation statements)

References 12 publications

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“…The existence of a positive Lyapunov exponent confirms the chaotic behavior of the system [38,39]. Lyapunov exponents (LEs) are necessary and more convenient for detecting hyperchaos in fractional order hyperchaotic system.…”

Section: Lyapunov Exponents and Kaplan-yorke Dimensionmentioning

confidence: 79%

Hyperchaotic Chameleon: Fractional Order FPGA Implementation

2017

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There are many recent investigations on chaotic hidden attractors although hyperchaotic hidden attractor systems and their relationships have been less investigated. In this paper, we introduce a hyperchaotic system which can change between hidden attractor and self-excited attractor depending on the values of parameters. Dynamic properties of these systems are investigated. Fractional order models of these systems are derived and their bifurcation with fractional orders is discussed. Field programmable gate array (FPGA) implementations of the systems with their power and resource utilization are presented.

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Section: Lyapunov Exponents and Kaplan-yorke Dimensionmentioning

confidence: 79%

Hyperchaotic Chameleon: Fractional Order FPGA Implementation

2017

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“…Chaotic random number generators have been implemented in FPGA for applications in image cryptography [44]. FPGA-implemented Duffing oscillatorbased signal detectors have been proposed by Rashtchi et al [45]. Digital implementations of chaotic multiscroll 6 Complexity attractors have been extensively investigated [41,46].…”

Section: Fpga Implementationmentioning

confidence: 99%

A Novel Approach to Numerical Modeling of Metabolic System: Investigation of Chaotic Behavior in Diabetes Mellitus

et al. 2018

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Although many mathematical models have been presented for glucose and insulin interaction, none of these models can describe diabetes disease completely. In this work, the dynamical behavior of a regulatory system of glucose-insulin incorporating time delay is studied and a new property of the presented model is revealed. This property can describe the diabetes disease better and therefore may help us in deeper understanding of diabetes, interactions between glucose and insulin, and possible cures for this widespread disease.

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“…Recently, Duffing chaotic oscillator has become a hotspot in the field of weak signal detection, because of its strong advantage of being immune to noise and irrelavant signals while highly sensitive to the signal whose frequency is close to the internal reference frequency [1,2,3] . To make the best use of Duffing oscillator, the determination of the critical threshold of reference amplitude and the indentification among chaotic state, intermittent chaotic state and large-scale periodic state are of great significance [4,5] . However, many researchers address these tasks by their experience, experiments and observing, instead of quantitative analysis, which limits the engineering application of their methods.…”

Section: Introductionmentioning

confidence: 99%

Weak Signal Detection with Duffing Oscillator Based on Circular Boundary Counting Method and STFT State Identification Parameter

Zhu¹,

Jia²,

Yan³

et al. 2019

Proceedings of the 2nd International Conference on Electrical and Electronic Engineering (EEE 2019)

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To solve the problem of quantitative identification of the state of Duffing oscillator and determination of the critical threshold of reference amplitude, a combined weak signal detection method is proposed in this paper. The STFT statistical characteristics of Duffing oscillator in chaotic state, intermittent state and large-scale periodic state is analyzed and based on it the state identification parameter is selected to quantitatively present the state of Duffing oscillator. The step change of the number of the phase points on the boundary of circular regions in the phase plane is shown and the circular boundary counting method is proposed to determine the critical threshold. Based on above research, the algorithm of the combined weak signal detection is given, which uses Runge-Kutta algorithm to calculate the Duffing system. Simulation results show that this combined method is not only accurate at low SNR, but also robust when noise condition is variable.

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FPGA Implementation of a Real-Time Weak Signal Detector Using a Duffing Oscillator

Cited by 45 publications

References 12 publications

Hyperchaotic Chameleon: Fractional Order FPGA Implementation

Hyperchaotic Chameleon: Fractional Order FPGA Implementation

A Novel Approach to Numerical Modeling of Metabolic System: Investigation of Chaotic Behavior in Diabetes Mellitus

Weak Signal Detection with Duffing Oscillator Based on Circular Boundary Counting Method and STFT State Identification Parameter

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