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Memristor-based hyper-chaotic circuit for image encryption

Chinese Physics B 2020年第11期29卷 259-270页

作者： Jiao-Jiao Chen Deng-Wei Yan Shu-Kai Duan Li-Dan Wang College of Electronic and Information Engineering Southwest UniversityChongqing 400715China Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Southwest UniversityChongqing 400715China Intelligent Transmission and Control Technology Joint Engineering Laboratory Chongqing 400715China Brain-inspired Computing and Intelligent Control Chongqing Key Laboratory Chongqing 400715China Chongqing Collaborative Innovation Center for Brain Science Chongqing 400715China School of Artificial Intelligence Southwest UniversityChongqing 400715China

The memristor is a kind of non-linear element with memory function,which can be applied to chaotic systems to increase signal randomness and *** this paper,a new four-dimensional hyper-chaotic system is designed based on a flux controlled memristor model,which can generate complex chaotic *** basic dynamic theory analysis and numerical simulations of the system,such as the stability of equilibrium points,the Lyapunov exponents and dimension,Poincare maps,the power spectrum,and the waveform graph prove that it has rich dynamic ***,the circuit implementation of this system is *** consistency of simulation program with integrated circuit emphasis(SPICE)simulation and numerical analysis proves the ability to generate ***,a new image encryption scheme is designed by using the memristor-based hyper-chaotic system proposed in this *** scheme involves a total of two *** using different security analysis factors,the proposed algorithm is compared with other image encryption schemes,including correlation analysis,information entropy,*** results show that the proposed image encryption scheme has a large key space and presents a better encryption effect.

关键词： memristor SPICE simulation hyper-chaotic system image encryption

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Kernel Least Mean Square with Tracking 36

Kernel Least Mean Square with Tracking

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第36届中国控制会议

作者： Wanli Wang Shiyuan Wang Guobing Qian Bo Yang College of Electronic and Information Engineering Southwest University Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing

ISBN: (纸本)9781538629185

Based on the Gaussian process(GP) regression,the relationship between the input-output pair can be modeled by the sum of the Gaussian noise and an unknown latent function evaluated on an input(LFEI).The acquisition of LFEI is thus essentially *** this paper,a novel algorithm called kernel least mean square with tracking(KLMS-T) is proposed to estimate *** on the existing kernel least mean square(KLMS) that is a simple and efficient kernel adaptive filtering algorithm,the proposed KLMS-T utilizes the framework of Bayesian inference to estimate LFEI from the function-space *** show that compared with LMS and KLMS,KLMS-T achieves better filtering performance in terms of the convergence rate and the steady state mean square error.

关键词： Gaussian process latent function kernel adaptive filter mean square error

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A Read and Write Method for Forgetting Memristor Crossbar Array with Long-term and Short-term Memory

A Read and Write Method for Forgetting Memristor Crossbar Ar...

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2021 International Conference on Neuromorphic Computing, ICNC 2021

作者： Wang, Yifan Chen, Ling Li, Chuandong College of Westa Chongqing Southwest University Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Chongqing China College of Electronic Information and Engineering Chongqing Southwest University Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Chongqing China

ISBN: (纸本)9781665412872

In this paper, time slot technology is designed based on the single forgetting memristor synapse with single voltage source to read and write the forgetting memristor crossbar array. The amplitude of the voltage source signal is used to set the corresponding long-term and short-term memory weights, and the circuit protection signal is used to improve the security of the nanoscale memristor crossbar array. By analyzing the forgetting properties of memristor synapses, the forgetting memristor crossbar array with long-term memory, short-term memory (LSM) and its corresponding read-write mode are demonstrated. Because the forgetting memristor crossbar array can store both long-term and short-term memories, the application of forgetting memristor crossbar array to image storage can show the spontaneous evolution of images. © 2021 IEEE.

关键词： Memristors

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Blood pressure monitoring via double sandwich-structured triboelectric sensors and deep learning models

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Nano Research 2022年第6期15卷 5500-5509页

作者： Xu Ran Fangyuan Luo Zhiming Lin Zhiyuan Zhu Chuanjun Liu Bin Chen Chongqing Key Laboratory of Non-linear Circuit and Intelligent Information Processing College of Electronic and Information EngineeringSouthwest UniversityChongqing 400715China Research Laboratory U.S.E.Co.Ltd.Shibuya-kuTokyo 150-0013Japan

Real-time blood pressure monitoring is essential for the timely diagnosis and treatment of cardiovascular *** traditional prediction methods estimate blood pressure by measuring multiple sets of physiological signals with energyconsuming ***,a continuous,cuffless and self-powered blood pressure monitoring system was developed based on a new double sandwich-structured triboelectric sensor and a novel blood pressure method estimation.A pyramid-patterned sensor based on the double sandwich structure realizes a sensitivity of 0.89 V/kPa in a linear range of 0–35 kPa,which is more than twice of the conventional single electrode *** sensor processes a low pressure detection limit of 1 g andfast response time of 32 ***,it can easily capture the pulse signal at the radial ***,a novel method for estimating blood pressure using pulse waves accompanied by the user’s background information was *** method measures only one set of pulse signals and is portable.A deep learning model with multi-network structures was developed to improve the estimation *** mean absolute error and standard deviation of error for systolic and diastolic blood pressure(SBP and DBP)estimations were 3.79±5.27 and 3.86±5.18 mmHg,*** work reveals a new sensing structure of triboelectric sensors and offers a novel method for blood pressure estimation.

关键词： triboelectric nanogenerator self-powered sensor blood pressure monitoring deep learning

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Recurrent Neural Network for Nonconvex Economic Emission Dispatch

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Journal of Modern Power Systems and Clean Energy 2021年第1期9卷 46-55页

作者： Jiayu Wang Xing He Junjian Huang Guo Chen Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information EngineeringSouthwest UniversityChongqing 400715China Key Laboratory of Machine Perception and Children's Intelligence Development Chongqing University of EducationChongqing 400067China School of Electrical Engineering and Computer Science University of NewcastleNewcastleNSW 2308Australia

In this paper, an economic emission dispatch(EED) model is developed to reduce fuel cost and environmental pollution emissions. Considering the development of new energy sources in recent years, the EED problem involves thermal units with the valve point effect and WTs. Meanwhile, it complies with demand constraint and generator capacity constraints. A recurrent neural network(RNN) is proposed to search for local optimal solution of the introduced nonconvex EED problem. The optimality and convergence of the proposed dynamic model are given. The RNN algorithm is verified on a power generation system for the optimization of scheduling and minimization of total cost. Moreover, a particle swarm optimization(PSO) algorithm is compared with RNN under the same problematic frame. Numerical simulation results demonstrate that the optimal scheduling given by RNN is more precise and has lower total cost than PSO. In addition, the dynamic variation of power load demand is considered and the power distribution of eight generators during 12 time periods is depicted.

关键词： Recurrent neural network(RNN) nonconvex economic emission dispatch optimization problem

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Accelerated Primal-Dual Projection Neurodynamic Approach With Time Scaling for Linear and Set Constrained Convex Optimization Problems

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IEEE/CAA Journal of Automatica Sinica 2024年第6期11卷 1485-1498页

作者： You Zhao Xing He Mingliang Zhou Tingwen Huang Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information EngineeringSouthwest UniversityChongqing 400715China School of Computer Science Chongqing UniversityChongqing 400044China Department of Mathematics Texas A&M University at QatarDoha 23874Qatar IEEE

The Nesterov accelerated dynamical approach serves as an essential tool for addressing convex optimization problems with accelerated convergence *** previous studies in this field have primarily concentrated on unconstrained smooth con-vex optimization *** this paper,on the basis of primal-dual dynamical approach,Nesterov accelerated dynamical approach,projection operator and directional gradient,we present two accelerated primal-dual projection neurodynamic approaches with time scaling to address convex optimization problems with smooth and nonsmooth objective functions subject to linear and set constraints,which consist of a second-order ODE(ordinary differential equation)or differential conclusion system for the primal variables and a first-order ODE for the dual *** satisfying specific conditions for time scaling,we demonstrate that the proposed approaches have a faster conver-gence *** only requires assuming convexity of the objective *** validate the effectiveness of our proposed two accel-erated primal-dual projection neurodynamic approaches through numerical experiments.

关键词： Accelerated projection neurodynamic approach lin-ear and set constraints projection operators smooth and nonsmooth convex optimization time scaling.

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A brief survey on dynamical systems with saturated impulses

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Journal of the Franklin Institute 2025年第10期362卷

作者： Hongjuan Wu Chuandong Li Zhilong He School of Computer Science and Engineering Chongqing Three Gorges University Chongqing 404120 PR China Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Southwest University Chongqing 400715 PR China College of Mathematics and System Science Xinjiang University Urumqi 830017 PR China

In this paper, the research results on dynamical systems with saturated impulses (DSSI) are reviewed. We emphasize on the fundamental results, and the recent progress of the saturated impulse theories and the typical applications. Four aspects of saturated impulse are surveyed. That is, the common DSSI models with the important definitions and lemmas, the basic ideas for dealing with the saturated impulses, the estimation of the domain of attraction (DOA) for DSSI, and the typical applications of DSSI. The typical applications contain the design of hybrid controller for dynamical systems, the consensus of multi-agent systems (MASs), and the stability analysis of neural networks (NNs) and other networked systems. Finally, the conclusions and some future research directions are given.

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Stability of Inertial Delayed Neural Networks Via Event-Triggered Impulsive Control

Stability of Inertial Delayed Neural Networks Via Event-Trig...

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2021 International Conference on Neuromorphic Computing, ICNC 2021

作者： Hong, Nan Zhang, Wei Zhang, Tianguang Southwest University Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Department of Electronics and Information Engineering Chongqing China

ISBN: (纸本)9781665412872

This paper studies the stability of inertial delayed neural networks via event-triggered impulsive control (ETIC), where impulsive instants are determined by an effective Lyapunov-based impulsive event triggered mechanism (IETM). Based on the IETM, the Zeno behavior is excluded and ensures the globally exponential stability and h-stability of the neural networks by constructing Lyapunov function and some different restrictive conditions. In addition, the delay term in inertial neural networks is well dealt with the two lemmas given in this paper. It is shown that inertial delayed neural networks can be stabilized through this event-triggered impulsive control. Finally, two numerical examples and their simulations are carried out to verify the effectiveness of this method. © 2021 IEEE.

关键词： Time delay

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An adaptive malicious punishment over secure distributed estimation under attacks 4

An adaptive malicious punishment over secure distributed est...

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4th IEEE International Conference on Computer and Communications, ICCC 2018

作者： Hua, Yi Hu, Limei Chen, Feng Department of Electronic and Information Engineering Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Southwest University Chongqing China

ISBN: (纸本)9781538683392

In this paper, we propose an adaptive malicious punishment DLMS algorithm to mitigate the adversarial attack. Two types of attacks are proposed in the WSNs. The adaptive threshold is designed to detect attacks. Then corresponding weight of malicious nodes can be reduced, due to the punishing factor. The simulations demonstrate that the proposed algorithm is robust to the adversarial attacks. © 2018 IEEE.

关键词： Component Detecting malicious nodes DLMS The adaptive threshold The malicious attack The punishing weight

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A Distributed Dynamic Resource Allocation Strategy in A Large-scale Micro-grids Group 6

A Distributed Dynamic Resource Allocation Strategy in A Larg...

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6th International Conference on information, Cybernetics, and Computational Social Systems, ICCSS 2019

作者： Fu, Zao He, Xing Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Southwest University Chongqing China

ISBN: (纸本)9781728158570

In this paper, a dynamic economic dispatch problem (DEDP) with renewable energy generators is studied. With the purpose of minimizing the cost of DEDP and optimally allocate the load demand among the interconnected generators considering ramp-rate limits and generation limits, an effective continuous-time distributed algorithm based on interior point methods and primal-dual methods is proposed. In order to overcome the drawbacks of the renewable energy, a parallel system composed with flywheel energy storage systems and renewable energy generators is proposed to work in a constant power output mode. In addition, the using of switched systems makes the optimal solution more accurate. The excellent performance of the proposed algorithm is verified by IEEE 30-bus system with the REG based simulation. © 2019 IEEE.

关键词： Continuous time systems

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