Multistable Dynamics in a Hopfield Neural Network Under Electromagnetic Radiation and Dual Bias Currents

Abstract This paper investigates a Hopfield neural network (HNN) under the simulation of external electromagnetic radiation and dual bias currents, in which the fluctuation of magnetic flux across the neuron membrane is used to emulate the influence of electromagnetic radiation. Utilizing conventional analytical methods, the basic properties of the proposed Hopfield neural network are discussed. Due to the addition of electromagnetic radiation and dual bias currents, the Hopfield neural network shows high sensitivity to system parameters and initial conditions. The proposed Hopfield neural network possesses multistability with periodic attractor, quasi-periodic attractor, chaotic attractor and transient chaotic attractor, and all of the attractors are hidden attractors because there is no equilibrium point in the system. In particular, when the neuron membrane magnetic flux is different, the system can present transient chaos with different chaotic times. More interestingly, with the change of system parameters, the proposed Hopfield neural network can exhibit parallel bifurcation behaviors. Finally, the Multisim simulation and hardware experiment results based on discrete electronic components are conducted to support the numerical ones. These results could give useful information to the study of nonlinear dynamic characteristics of the Hopfield neural network.

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Design and FPGA Implementation of a Pseudo-random Number Generator Based on a Hopfield Neural Network Under Electromagnetic Radiation

Frontiers in Physics ◽

10.3389/fphy.2021.690651 ◽

2021 ◽

Vol 9 ◽

Author(s):

Fei Yu ◽

Zinan Zhang ◽

Hui Shen ◽

Yuanyuan Huang ◽

Shuo Cai ◽

...

Keyword(s):

Neural Network ◽

Electromagnetic Radiation ◽

Random Number ◽

Random Number Generator ◽

Hopfield Neural Network ◽

Feedback Controller ◽

Chaotic Oscillator ◽

Number Generator ◽

Pseudo Random Number ◽

Pseudo Random Number Generator

When implementing a pseudo-random number generator (PRNG) for neural network chaos-based systems on FPGAs, chaotic degradation caused by numerical accuracy constraints can have a dramatic impact on the performance of the PRNG. To suppress this degradation, a PRNG with a feedback controller based on a Hopfield neural network chaotic oscillator is proposed, in which a neuron is exposed to electromagnetic radiation. We choose the magnetic flux across the cell membrane of the neuron as a feedback condition of the feedback controller to disturb other neurons, thus avoiding periodicity. The proposed PRNG is modeled and simulated on Vivado 2018.3 software and implemented and synthesized by the FPGA device ZYNQ-XC7Z020 on Xilinx using Verilog HDL code. As the basic entropy source, the Hopfield neural network with one neuron exposed to electromagnetic radiation has been implemented on the FPGA using the high precision 32-bit Runge Kutta fourth-order method (RK4) algorithm from the IEEE 754-1985 floating point standard. The post-processing module consists of 32 registers and 15 XOR comparators. The binary data generated by the scheme was tested and analyzed using the NIST 800.22 statistical test suite. The results show that it has high security and randomness. Finally, an image encryption and decryption system based on PRNG is designed and implemented on FPGA. The feasibility of the system is proved by simulation and security analysis.

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Parameter-Independent Dynamical Behaviors in Memristor-Based Wien-Bridge Oscillator

Mathematical Problems in Engineering ◽

10.1155/2017/5897286 ◽

2017 ◽

Vol 2017 ◽

pp. 1-13 ◽

Cited By ~ 4

Author(s):

Ning Wang ◽

Bocheng Bao ◽

Tao Jiang ◽

Mo Chen ◽

Quan Xu

Keyword(s):

Chaotic Attractor ◽

Initial Conditions ◽

System Model ◽

Phase Portraits ◽

Transient Chaos ◽

Chaotic Oscillator ◽

Initial Condition ◽

Bifurcation Diagrams ◽

System Parameters ◽

Dynamical Behaviors

This paper presents a novel memristor-based Wien-bridge oscillator and investigates its parameter-independent dynamical behaviors. The newly proposed memristive chaotic oscillator is constructed by linearly coupling a nonlinear active filter composed of memristor and capacitor to a Wien-bridge oscillator. For a set of circuit parameters, phase portraits of a double-scroll chaotic attractor are obtained by numerical simulations and then validated by hardware experiments. With a dimensionless system model and the determined system parameters, the initial condition-dependent dynamical behaviors are explored through bifurcation diagrams, Lyapunov exponents, and phase portraits, upon which the coexisting infinitely many attractors and transient chaos related to initial conditions are perfectly offered. These results are well verified by PSIM circuit simulations.

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Hidden extreme multistability with hyperchaos and transient chaos in a Hopfield neural network affected by electromagnetic radiation

Nonlinear Dynamics ◽

10.1007/s11071-019-05408-5 ◽

2019 ◽

Vol 99 (3) ◽

pp. 2369-2386 ◽

Cited By ~ 22

Author(s):

Hairong Lin ◽

Chunhua Wang ◽

Yumei Tan

Keyword(s):

Neural Network ◽

Electromagnetic Radiation ◽

Hopfield Neural Network ◽

Transient Chaos ◽

Extreme Multistability ◽

Hidden Extreme Multistability

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ON THE GLOBAL ASYMPTOTIC STABILITY ANALYSIS OF DELAYED NEURAL NETWORKS

International Journal of Bifurcation and Chaos ◽

10.1142/s0218127405014453 ◽

2005 ◽

Vol 15 (12) ◽

pp. 4019-4025 ◽

Cited By ~ 8

Author(s):

ZHAOHUI YUAN ◽

DEWEN HU ◽

LIHONG HUANG ◽

GUOHUA DONG

Keyword(s):

Neural Network ◽

Asymptotic Stability ◽

Global Asymptotic Stability ◽

Hopfield Neural Network ◽

Cellular Neural Network ◽

Functional Method ◽

Activation Functions ◽

Delayed Neural Networks ◽

System Parameters ◽

Lyapunov Functional Method

In this paper, the problem of the global asymptotic stability (GAS) of a class of delayed neural network is investigated. Under the generalization of dropping the boundedness and differentiability hypotheses for activation functions, using some existing results for the existence and uniqueness of the equilibrium point, we obtain a couple of general results concerning GAS by means of Lyapunov functional method without the assumption of symmetry of interconnection matrix. Our results improve and extend some previous works of other researchers. Moreover, our conditions are presented in terms of system parameters, which have leading significance in designs and applications of GAS for Hopfield neural network (HNNs) and delayed cellular neural network (DCNNs).

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Effect of the delay on the boundary of the basin of attraction in a Hopfield neural network system

PsycEXTRA Dataset ◽

10.1037/e429062008-001 ◽

2008 ◽

Keyword(s):

Neural Network ◽

Basin Of Attraction ◽

Hopfield Neural Network ◽

Network System ◽

Neural Network System ◽

The Basin Of Attraction

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Biological effects of low-intensity radiofrequency fields and risk assessment for biota

Russian Journal of Occupational Health and Industrial Ecology ◽

10.31089/1026-9428-2020-60-9-592-596 ◽

2020 ◽

Vol 60 (9) ◽

pp. 592-596

Author(s):

Elena I. Sarapultseva ◽

Darya V. Uskalova ◽

Ksenya V. Ustenko

Keyword(s):

Radio Frequency ◽

Electromagnetic Radiation ◽

Electromagnetic Fields ◽

Negative Impact ◽

Biological Effects ◽

High Sensitivity ◽

Communication Technologies ◽

Natural Ecosystems ◽

Low Intensity ◽

Different Levels

Despite the fact that there are still conflicting opinions about the damage caused by modern wireless communication technologies, most scientists report on the negative biological effects of low-intensity radio frequency electromagnetic radiation at different levels of the organization of live nature. There is no doubt that there is a need not only for a sanitary and hygienic assessment of man-made electromagnetic effects on humans, but also for an environmental assessment for biota. The purpose of the study was to assess the potential environmental risk of electromagnetic impact in the centimeter range on natural ecosystems. The initial data were the authors' own results in the field of radiobiology of non-ionizing radiation, as well as published of other researchers. The article analyzes the biological effects of radio frequency electromagnetic fields detected in organisms of different systematic groups and levels of organization. The data on the non-thermal biological effects of electromagnetic fields indicate a high sensitivity of different species to this factor. The analyzed research results emphasize the need to take into account the features of non-thermal effects of electromagnetic radiation on biota, since these radiations can have a negative impact on different hierarchical levels in natural ecosystems.

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