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Retraction Note: A defensive design for control application based on networked systems

Soft Computing 2024年第2期28卷 1003-1003页

作者： Rajput, Ahmed Raza Aslam, Muhammad Shamrooz Li, Qianmu Qaisar, Irfan Niazi, Shahab Ahmad School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing P.R. China School of Electrical and Information Engineering Guangxi University of Science and Technology Liuzhou P.R. China Department of Automation Tsinghua University Beijing P.R. China Department of Electronic Engineering The Islamia University of Bahawalpur Bahawalpur Pakistan

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Low-Cost Approach for Improving Video Transmission Efficiency in WVSN

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Journal of Shanghai Jiaotong university(Science) 2020年第5期25卷 600-605页

作者： LIU Min DENG Bin TANG Ying WU Minghu WANG Juan Hubei Key Laboratory for High-Efficiency Utilization of Solar Energy and Operation Control of Energy Storage System.Hubei University of Technology Wuhan 430068.China Department of Electrical and Computer Engineering.Rowan University GlassboroNJ 08028USA State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Institute of Smart Education Qingdao Academy of Intelligent IndustriesQingdao 266041ShandongChina

The wireless visual sensor network(WVSN)as a new emerged intelligent visual system,has been applied in many video monitoring ***,there is still great challenge because of the limited wireless network *** resolve the problem,we propose a real-time dynamic texture approach which can detect and reduce the temporal redundancy during many successive image ***,an adaptively learning background model is improved to discover successive similar image frames from the inputting video ***,the dynamic texture model based on the singular value decomposition is adopted to distinguish foreground and background element ***,a background discarding strategy based on visual motion coherence is proposed to determine whether each image frame is streamed or *** evaluate the trade-off performance of the proposed method,it is tested on the CDW-2014 dataset,which can accurately detect the first foreground frame when the moving objects of interest appear in the field of view in the most tested dynamic scenes,and the misdetection rate of the undetected foreground frames is near to *** to the original stream,it can reduce the occupied bandwidth a lot and its computational cost is relatively lower than the state-of-the-art methods.

关键词： wireless visual sensor network(WVSN) temporal redundancy foreground background dynamic texture

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Active fault detection for spacecraft attitude control system

Active fault detection for spacecraft attitude control syste...

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Chinese control Conference (CCC)

作者： Qun Zong Xicheng Yang Xiuyun Zhang Wenjing Liu School of Electrical Engineering and Automation Tianjin P. R. China Science and Technology on Space Intelligent Control Laboratory Beijing Institute of Control Engineering Beijing China

ISBN: (数字)9789881563903

ISBN: (纸本)9781728165233

This paper proposed an active fault detection (AFD) method to detect the incipient fault occurred in the spacecraft system. Since there's no abnormal change in the characteristic of the incipient fault system, AFD can be carried out by injecting a designed excitation signal into the system to activate the minor fault signature. Based on the Youla parametrization, the closed-loop residual signal and the performance criteria are constructed. Then the excitation signal of AFD is optimized to not only realize incipient fault detection, but also affect the system as little as possible. What's more, the residual evaluation function and the threshold are designed to guarantee the robustness of the proposed AFD method to the external disturbances, which can prevent the false alarms and omission of the incipient fault. The comparative simulations are carried out to verify the efficiency of the proposed method.

关键词： Space vehicles Fault detection Robustness Adaptive control Mathematical model Transfer functions Observers

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A Simple Computational Model of Light-sensitive Cardiac tissue for Simulation of the optogenetic Defibrillation 26

A Simple Computational Model of Light-sensitive Cardiac tiss...

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26th National and 4th International Iranian Conference on Biomedical engineering, ICBME 2019

作者： Zafarghandi, Elham Zakeri Bahrami, Fariba School of Electrical and Computer Engineering College of Engineering University of Tehran Human Motor Control and Computational Neuroscience Laboratory Tehran Iran

ISBN: (纸本)9781728156637

Atrial and ventricular fibrillations are two types of severe heart arrhythmias. As have claimed in Karathanos et al. (2014 and 2016), and Boyle et al. (2015) optogenetic treatments are considered as a convincing substitute for cardiac therapies. However, investigating these techniques under different constraints and the condition of in vivo testing is not always straight-forward. Computational modeling can be used as the first step before any experimental study. The objective of this study is to modify and simplify an already developed cardiac cell model of Ten Tusscher in order to simulating an optogenetic cardiac tissue in silico. In the original model Action Potential (AP) generation in each cardiac cell is described by a dynamic model of order 17. We estimated the parameters of a second-order Aliev-Panfilov model such that it can mimic the behavior of both light-sensitive and normal cardiac cells. Then we showed that the electrophysiological behavior of the new model of the tissue (consisted of 128∗128 cells) is similar to the original complex model. The criteria for comparing the behavior of the two models is their ability to generate the spiral waves representing cardiac tissue fibrillation and also the characteristics of these spiral waves. Afterwards, the model is used to predict the propagation of the spiral waves on the tissue, and to describe the function of the optogenetic cells used to defibrillate a stable-induced spiral wave. © 2019 IEEE.

关键词： Tissue

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Deep Transfer Learning-based Fault Diagnosis of Spacecraft Attitude System

Deep Transfer Learning-based Fault Diagnosis of Spacecraft A...

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Chinese control Conference (CCC)

作者： Yifan Tang Liqian Dou Ruilong Zhang Xiuyun Zhang Wenjing Liu School of Electrical Engineering and Automation Tianjin P. R. China Science and Technology on Space Intelligent Control Laboratory Beijing Institute of Control Engineering Beijing China

ISBN: (数字)9789881563903

ISBN: (纸本)9781728165233

In recent years, an increasingly popularity of deep learning model for intelligent state monitoring, diagnosis and prediction of spacecraft has been observed. However, in the previous studies, a major assumption accepted by default is that source domain data and target domain data have same feature distribution. Unfortunately, this assumption is mostly invalid in real application. Considering the problem that the original fault data sample is small, the noise is high and the fault signal is unlabeled, in this paper, we propose deep transfer learning-based fault diagnosis method for spacecraft system in which a new fault diagnosis framework-deep transfer network(DTN) is built, and it can generalize deep learning model to domain adaptation scenario inspired by the idea of transfer learning. In order to improve the accuracy of on-orbit spacecraft fault data detection, the proposed framework with joint distribution adaptation(JDA) is applied to exploit the distribution structure of unlabeled data in target domain by using the data with labels in source domain. By comparing with other methods, the deep transfer network based on joint distribution adaptation has better transfer performance in fault diagnosis of spacecraft.

关键词： Space vehicles Fault diagnosis Data models Neural networks Feature extraction Adaptation models Mathematical model

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Learning-Based Energy-Efficient Channel Selection for Edge Computing-Empowered Cognitive Machine-to-Machine Communications 91

Learning-Based Energy-Efficient Channel Selection for Edge C...

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91st IEEE Vehicular Technology Conference, VTC Spring 2020

作者： Liao, Haijun Zhou, Zhenyu Ai, Bo Guizani, Mohsen North China Electric Power University State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Electric and Electronic Engineering Beijing China Beijing Jiaotong University State Key Laboratory of Rail Traffic Control and Safety Beijing China University of Idaho Electrical and Computer Engineering Department Moscow United States

ISBN: (数字)9781728152073

ISBN: (纸本)9781728152073

In this paper, we study the channel selection problem in edge computing-empowered cognitive machine-to-machine (CM2M) communications, where a massive number of machine type devices (MTDs) offload their computational tasks to a nearby edge server by opportunistically using the spectra that are temporarily unoccupied by primary users (PUs). We formulate the channel selection problem as an adversarial multi-armed bandit (MAB) problem, and combine the exponential-weight algorithm for exploration and exploitation (EXP3) and Lyapunov optimization to develop a learning-based energy-efficient solution named SEB-EXP3. It can find the long-term optimal channel selection strategy with guaranteed performance based on local information, while simultaneously achieving service reliability awareness, energy awareness, and data backlog awareness. Four heuristic algorithms are compared with SEB-EXP3 to demonstrate its effectiveness and reliability under various simulation settings. © 2020 IEEE.

关键词： Edge computing

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Algal Bloom Front Tracking Using an Unmanned Surface Vehicle: Numerical Experiments Based on Baltic Sea Data

Algal Bloom Front Tracking Using an Unmanned Surface Vehicle...

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OCEANS

作者： Joana Fonseca Miguel Aguiar João Borges de Sousa Karl H. Johansson Division of Decision and Control Systems School of Electrical Engineering and Computer Science and Digital Futures KTH Royal Institute of Technology Stockholm Sweden Underwater Systems and Technology Laboratory (LSTS) University of Porto Portugal

ISBN: (纸本)9781665427883

We consider the problem of tracking moving algal bloom fronts using an unmanned surface vehicle (USV) equipped with a sensor that measures the concentration of chlorophyll a. Chlorophyll a is a green pigment found in plants, and its concentration is an indicator of phytoplankton abundance. Our algal bloom front tracking mission consists of three stages: deployment, data collection, and front tracking. At the deployment stage, a satellite collects an image of the sea from which the location of the front, the reference value for the concentration at this front and, consequently, the appropriate initial position for the USV are determined. At the data collection stage, the USV collects data points to estimate the local algal gradient as it crosses the front. Finally, at the front tracking stage, an adaptive algorithm based on recursive least squares fitting using recent past sensor measures is executed. We evaluate the performance of the algorithm and its sensitivity to measurement noise through MATLAB simulations. We also present an implementation of the algorithm on the DUNE onboard software platform for marine robots and validate it using simulations with satellite model forecasts from Baltic sea data.

关键词： Water Temperature measurement Satellites Software algorithms Sea measurements Predictive models Robot sensing systems

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Parameter training methods for convolutional neural networks with adaptive adjustment method based on Caputo fractional-order differences

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Chaos, Solitons and Fractals 2025年 199卷

作者： Zhao, Haiming Yang, Honggang Chen, Jiejie Jiang, Ping Zeng, Zhigang School of Computer and Information Engineering Hubei Normal University Huangshi435000 China School of Automation Wuhan University of Technology Wuhan430000 China School of Computer Hubei Polytechnic University Huangshi435000 China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430000 China Key Laboratory of Image Information Processing and Intelligent Control Ministry of Education of China Wuhan430000 China

As deep learning technologies continue to permeate various sectors, optimization algorithms have become increasingly crucial in neural network training. This paper introduces two adaptive momentum algorithms based on Grünwald–Letnikov and Caputo fractional-order differences—Fractional Order Adagrad (FAdagrad) and Fractional Order Adam (FAdam)—to update parameters more flexibly by adjusting momentum information. Commencing from the definitions of fractional derivatives, we propose integrating fractional-order differences with gradient algorithms in convolutional neural networks (CNNs). These adaptive momentum algorithms, leveraging Grünwald–Letnikov and Caputo fractional-order differences, offer enhanced flexibility, thereby accelerating convergence. Our nonlinear parameter tuning method for CNNs demonstrates superior performance compared to traditional integer-order momentum algorithms and the standard Adam algorithm. Experimental results on the BraTS2021 dataset and CIFAR-100 dataset reveal that the proposed fractional-order optimization algorithms significantly outperform their integer-order counterparts in model optimization. They not only expedite convergence but also improve the accuracy of image recognition and segmentation. © 2025 Elsevier Ltd

关键词： Convolutional neural networks

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Tier Partitioning and Flip-flop Relocation Methods for Clock Trees in Monolithic 3D ICs

Tier Partitioning and Flip-flop Relocation Methods for Clock...

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2019 IEEE/ACM International Symposium on Low Power Electronics and Design, ISLPED 2019

作者： Shim, Da Eun Pentapati, Sai Lee, Jeehyun Yu, Yun Seop Kyu Lim, Sung School of Electrical and Computer Engineering Georgia Institute of Technology United States Department of Electrical Electronic and Control Engineering Hankyong National University Korea Republic of

ISBN: (纸本)9781728129549

In this paper, we propose simple but effective clock tree optimization algorithms for monolithic 3D ICs that are based on tier partitioning and flip-flop relocation. Our algorithms take into account 3D timing critical paths, clock skew, and the clock tree hierarchy for a better quality 3D clock tree. We also perform clock slew manipulation and buffer reduction to further improve the 3D designs. We tested four industrial benchmarks implemented using a commercial library and observed up to 34.3% clock skew, 35.9% clock wirelength, 10.0% combinational clock power, and 15.5% total power savings compared to the state-of-the-art [8]. © 2019 IEEE.

关键词： Flip flop circuits

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An Universal control Strategy for Planar 2-DoF Underactuated Manipulator with One Passive Joint

An Universal Control Strategy for Planar 2-DoF Underactuated...

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第40届中国控制会议

作者： Zixin Huang Yaosheng Zhou Zhen Chen Wei Wang Lejun Wang School of Electrical and Information Engineering Wuhan Institute of Technology Hubei Key Laboratory of Digital Textile Equipment Wuhan Textile University Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Innovation and Entrepreneurship Wuhan Institute of Technology School of Information and Safety Engineering Zhongnan University of Economics and Law

This paper presents an unified control strategy based on the trajectory planning and tracking control for the planar 2-Do F underactuated manipulator. The trajectory of the active link is composed of two parts. The first part trajectories are designed according to the initial and target angles of the active link. The second part trajectories are designed based on the constraints between the underactuated link and the active link. Meanwhile, the parameters of the trajectories are optimized by the differential evolution algorithm(DEA) to ensure all links eventually reach to their target values by tracking the designed trajectories. Then,the sliding mode variable structure controller are designed to make the active link track their trajectories. The effectiveness of such strategy is demonstrated through simulation results.

关键词： Planar 2-DoF underactuated manipulator Trajectory planning Tracking control Differential evolution algorithm

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