Electronic circuit design, implementation and FPGA-based realization of a new 3D chaotic system with single equilibrium point

Tuna, Murat; Fidan, Can Bülent

doi:10.1016/j.ijleo.2016.09.087

Cited by 48 publications

(47 citation statements)

References 20 publications

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“…e Runge-Kutta algorithm is better than other algorithms in operation effect, with high accuracy, stable calculation process, and easy realization. RK-4 is easier to implement than RK-5, so RK-4 is widely used to solve chaotic systems [103]. Equation (12) gives the formula for calculating K 1 , K 2 , K 3 , and K 4 , which represents the slope value of [y 0 , y i ]:…”

Section: The Fpga-based Model Of the Novel 5d Hfwmsmentioning

confidence: 99%

Analysis and FPGA Realization of a Novel 5D Hyperchaotic Four‐Wing Memristive System, Active Control Synchronization, and Secure Communication Application

Liu

et al. 2019

Complexity

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By introducing a flux-controlled memristor with quadratic nonlinearity into a 4D hyperchaotic system as a feedback term, a novel 5D hyperchaotic four-wing memristive system (HFWMS) is derived in this paper. The HFWMS with multiline equilibrium and three positive Lyapunov exponents presented very complex dynamic characteristics, such as the existence of chaos, hyperchaos, limit cycles, and periods. The dynamic characteristics of the HFWMS are analyzed by using equilibria, phase portraits, poincare map, Lyapunov exponential spectrum, bifurcation diagram, and spectral entropy. Of particular interest is that this novel system can generate two-wing hyperchaotic attractor under appropriate parameters and initial conditions. Moreover, the FPGA realization of the novel 5D HFWMS is reported, which prove that the system has complex dynamic behavior. Finally, synchronization of the 5D hyperchaotic system with different structures by active control and a secure signal masking application of the HFWMS are implemented based on numerical simulations and FPGA. This research demonstrates that the hardware-based design of the 5D HFWMS can be applied to various chaos-based embedded system applications including random number generation, cryptography, and secure communication.

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Section: The Fpga-based Model Of the Novel 5d Hfwmsmentioning

confidence: 99%

Analysis and FPGA Realization of a Novel 5D Hyperchaotic Four‐Wing Memristive System, Active Control Synchronization, and Secure Communication Application

Liu

et al. 2019

Complexity

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“…The signals produced by many chaotic systems have ergodic and stochastic features. That is why chaotic signals can be used as an entropy source, substituted for random signals …”

Section: Basic Conceptsmentioning

confidence: 99%

“…That is why chaotic signals can be used as an entropy source, substituted for random signals. 7,19,20 Besides, chaos has become a widespread subject that has been studied nearly in every disciplines like astronomy, biology, physics, chemistry, engineering sciences, geology, mathematics, medicine, meteorology, and even social sciences. [21][22][23][24][25][26][27][28][29] There are many methods to investigate if a dynamic system exhibits chaotic feature or not.…”

Section: Chaosmentioning

confidence: 99%

A novel high speed Artificial Neural Network–based chaotic True Random Number Generator on Field Programmable Gate Array

Alçın

Koyuncu

Tuna

et al. 2018

Circuit Theory & Apps

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Summary It is well observed that cryptographic applications have great challenges in guaranteeing high security as well as high throughput. Artificial neural network (ANN)–based chaotic true random number generator (TRNG) structure has not been unprecedented in current literature. This paper provides a novel type of high‐speed TRNG based on chaos and ANN implemented in a Xilinx field‐programmable gate array (FPGA) chip. The paper consists of two main parts. In the first part, chaos analyses of Pehlivan‐Uyaroglu_2010 chaotic system (PUCS) have been accomplished to prove that PUCS operates in chaotic regime. So PUCS can be an efficient alternative to the entropy source for classical TRNGs. In the second part, the hardware design of the proposed TRNG has been created using VHDL in Xilinx platform. As a result, the implemented TRNG offers throughput up to 115.794 Mbps. Besides, the generated random numbers have been tested with the FIPS 140‐1 and NIST 800.22 test suites. The high quality of generated true random numbers have been confirmed by passing all randomness tests. The results have shown that the proposed system can provide not only high throughput but also high quality random bit sequences for a wide variety of embedded cryptographic applications.

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“…In other words, starting from random or different initial states, all the real-time states of the response, i.e., slave chaotic sensor systems are forced to track all the real-time states of the drive, i.e., master chaotic sensor systems. The synchronization of chaotic sensor systems has numerous practical applications, such as secure communications [15,16], sensor systems [17], finance systems [18] and electronic systems [19], ecological systems [20], and many other engineering systems [21]. Moreover, various feasible real sensing applications in the fields of sensing and chaotic sensor systems have been reported [22,23,24,25,26,27,28,29].…”

Section: Introductionmentioning

confidence: 99%

Rejecting Chaotic Disturbances Using a Super-Exponential-Zeroing Neurodynamic Approach for Synchronization of Chaotic Sensor Systems

Chen

2018

Sensors

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Due to the existence of time-varying chaotic disturbances in complex applications, the chaotic synchronization of sensor systems becomes a tough issue in industry electronics fields. To accelerate the synchronization process of chaotic sensor systems, this paper proposes a super-exponential-zeroing neurodynamic (SEZN) approach and its associated controller. Unlike the conventional zeroing neurodynamic (CZN) approach with exponential convergence property, the controller designed by the proposed SEZN approach inherently possesses the advantage of super-exponential convergence property, which makes the synchronization process faster and more accurate. Theoretical analyses on the stability and convergence advantages in terms of both faster convergence speed and lower error bound within the task duration are rigorously presented. Moreover, three synchronization examples substantiate the validity of the SEZN approach and the related controller for synchronization of chaotic sensor systems. Comparisons with other approaches such as the CZN approach, show the convergence superiority of the proposed SEZN approach. Finally, extensive tests further investigate the impact on convergence performance by choosing different values of design parameter and initial state.

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Electronic circuit design, implementation and FPGA-based realization of a new 3D chaotic system with single equilibrium point

Cited by 48 publications

References 20 publications

Analysis and FPGA Realization of a Novel 5D Hyperchaotic Four‐Wing Memristive System, Active Control Synchronization, and Secure Communication Application

Analysis and FPGA Realization of a Novel 5D Hyperchaotic Four‐Wing Memristive System, Active Control Synchronization, and Secure Communication Application

A novel high speed Artificial Neural Network–based chaotic True Random Number Generator on Field Programmable Gate Array

Rejecting Chaotic Disturbances Using a Super-Exponential-Zeroing Neurodynamic Approach for Synchronization of Chaotic Sensor Systems

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