A 4D Trigonometric-Based Memristor Hyperchaotic Map to Ultra-Fast PRNG

Xu, Bo; Luo, Xiaowei; Wang, Yifan; Bai, Libing; Chen, Kai; Zhao, Jia

doi:10.1109/tii.2024.3372017

Cited by 2 publications

(2 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There is also the UFPRNG (Ultra-Fast Pseudorandom Number Generator), which is based on 4D-TBMHM and ALFSR and is validated by the NIST statistical test and TestU01 [15]. In addition to those mentioned, there are PRNG generators that use ANNs (Artificial Neural Networks) such as the one proposed in [16].…”

Section: −mentioning

confidence: 99%

Design of a New Neuro-Generator with a Neuronal Module to Produce Pseudorandom and Perfectly Pseudorandom Sequences

Rivas Becerra,

Panduro,

Ortega Cisneros

et al. 2024

Electronics

View full text Add to dashboard Cite

This paper presents the design of a new neuro-generator of pseudorandom number type PRNG Pseudorandom Number Generator, which produces complex sequences with an adequate bit distribution. The circuit is connected to a neuronal module with six impulse neurons with different behaviors: spike frequency adaptation, phasic spiking, mixed mode, phasic bursting, tonic bursting and tonic spiking. This module aims to generate a non-periodic signal that becomes the clock signal for one of the LFSRs Linear Feedback Shift Register that the neuro-generator has. To verify its correct operation, the neuro-generator was subjected to a series of tests where the frequencies of the impulse neurons were modified. This modification allows the generation of a greater number of pulses at the output of the neuronal module, to obtain sequences with different characteristics that pass different NIST statistical tests (National Institute of Standards and Technology of U.S.). The results show that the new neuro-generator maintains pseudo-randomness in the sequences obtained with different frequencies and it can be implemented on a reconfigurable FPGA Field Programmable Gate Array Virtex 7 xc7vx485t-2ffg1761 device. Therefore, it can be used for applications such as biological systems.

show abstract

Section: −mentioning

confidence: 99%

Design of a New Neuro-Generator with a Neuronal Module to Produce Pseudorandom and Perfectly Pseudorandom Sequences

Rivas Becerra,

Panduro,

Ortega Cisneros

et al. 2024

Electronics

View full text Add to dashboard Cite

show abstract

“…Additionally, numerous studies have indicated that discrete memristor systems are more straightforward to design for hyperchaotic systems [24,32,33]. Xu et al proposed a novel fourdimensional discrete memristive system based on discrete memristors, which can generate diverse singular attractors with complex fractal structures and exceptional performance indicators, especially the attractors of hyperchaos [34]. Lai et al constructed a local active discrete memristor and used it to study the effect of electromagnetic radiation on neuronal dynamics.…”

Section: Introductionmentioning

confidence: 99%

Dynamical analysis of a novel memristor-type chaotic map

Yu,

Abu Bakar,

et al. 2024

Phys. Scr.

View full text Add to dashboard Cite

As a unique nonlinear component, the discrete memristor, with its simple structure, is associated with the ability to lead to excellent chaotic performance in the construction of chaotic systems. This characteristic has elevated the discrete memristor to a hot topic in the field of chaos. This paper introduces a cosine hyperchaotic map. Numerical simulations reveal its rich dynamical behaviors. The chaotic map exhibits diverse chaotic control models, including partial amplitude control, total amplitude control, initial boosting, and parameter-offset boosting, with dynamical distribution diagram plotted for amplitude control to quantify the range of amplitude modulation. Additionally, a localized boosting free region is identified, and dual offset parameters are introduced to control this localized boosting free region, enhancing the flexibility of the system. Finally, the map is implemented on STM32 to validate the numerical simulation results.

show abstract

A 4D Trigonometric-Based Memristor Hyperchaotic Map to Ultra-Fast PRNG

Cited by 2 publications

References 35 publications

Design of a New Neuro-Generator with a Neuronal Module to Produce Pseudorandom and Perfectly Pseudorandom Sequences

Design of a New Neuro-Generator with a Neuronal Module to Produce Pseudorandom and Perfectly Pseudorandom Sequences

Dynamical analysis of a novel memristor-type chaotic map

Contact Info

Product

Resources

About