检索结果-内蒙古大学图书馆

Robust Normalized Least Mean Absolute Third Algorithms

IEEE ACCESS 2019年 7卷 10318-10330页

作者： Xiong, Kui Wang, Shiyuan Chen, Badong Southwest Univ Coll Elect & Informat Engn Chongqing 400715 Peoples R China Chongqing Key Lab Nonlinear Circuits & Intelligen Chongqing 400715 Peoples R China Xi An Jiao Tong Univ Inst Artificial Intelligence & Robot Xian 710049 Shaanxi Peoples R China

This paper addresses the stability issues of the least mean absolute third (LMAT) algorithm using the normalization based on the third order in the estimation error. A novel robust normalized least mean absolute third (RNLMAT) algorithm is therefore proposed to be stable for all statistics of the input, noise, and initial weights. For further improving the filtering performance of RNLMAT in different noises and initial conditions, the variable step-size RNLMAT (VSSRNLMAT) and the switching RNLMAT (SWRNLMAT) algorithms are proposed using the statistics of the estimation error and a switching method, respectively. The filtering performance of RNLMAT is improved by VSSRNLMAT and SWRNLMAT at the expense of affordable computational cost. RNLMAT with less computational complexity than other normalized adaptive filtering algorithms, can provide better filtering accuracy and robustness against impulsive noises. The steady-state performance of RNLMAT and SWRNLMAT in terms of the excess mean-square error is performed for theoretical analysis. Simulations conducted in system identification under different noise environments confirm the theoretical results and the superiorities of the proposed algorithms from the aspects of filtering accuracy and robustness against large outliers.

关键词： Least mean absolute third algorithm normalization robustness variable step-size switching performance analysis impulsive noise

来源：评论

学校读者我要写书评

暂无评论

Toward Constructing a Real-time Social Anxiety Evaluation System: Exploring Effective Heart Rate Features

引用

IEEE TRANSACTIONS ON AFFECTIVE COMPUTING 2020年第1期11卷 100-110页

作者： Wen, Wanhui Liu, Guangyuan Mao, Zhi-Hong Huang, Wenjin Zhang, Xu Hu, Hui Yang, Jiemin Jia, Wenyan Southwest China Univ Chongqing Key Lab Nonlinear Circuits & Intelligen Chongqing 400715 CO Peoples R China Southwest China Univ Sch Elect & Informat Engn Chongqing 400715 CO Peoples R China Univ Pittsburgh Dept Elect & Comp Engn Pittsburgh PA 15261 USA Univ Pittsburgh Dept Bioengn Pittsburgh PA 15261 USA Southwest China Univ Coll Psychol Chongqing 400715 CO Peoples R China Univ Pittsburgh Dept Neurol Surg Pittsburgh PA 15213 USA

Social anxiety is a negative emotion which may impair the health of the heart and social functioning of an individual. This work analyzes the influence of social anxiety on the autonomic nerve control of the heart in two social exposure events: public speaking and thesis defending. In an experiment of public speaking, 59 human subjects were tested, and 11 conventional heartbeat measures and a heartbeat measure named the range of local Hurst exponents (RLHE) were evaluated for their capabilities to reveal the onset of social anxiety. Two-sample t-test between the baseline data and high anxiety data shows that social anxiety significantly reduces the complexity of the heartbeats. In an experiment of thesis defense, heartbeats data were acquired from nine graduate students. With the combination of three conventional features and the RLHE feature, a support vector machine classifier obtained true positive rate and true negative rate of 84.88 and 97.29 percent in the five-fold cross validation process of binary classification between high anxiety status and low anxiety status;the classifier also realized a generalization accuracy of 81.82 percent in detecting the high anxiety status in the thesis defense. A real-time anxiety monitoring system was established based on the above anxiety detecting method.

关键词： Electrocardiography Heart beat Public speaking Biomedical monitoring Speech Complexity theory Heart rate local Hurst exponents psychophysiological reactivity social anxiety

来源：评论

学校读者我要写书评

暂无评论

Ultrasonic Lamb Wave Damage Detection of CFRP Composites Using the Bayesian Neural Network

引用

JOURNAL OF NONDESTRUCTIVE EVALUATION 2024年第2期43卷 48-48页

作者： Luo, Kai Zhu, Jiayin Li, Zhenliang Zhu, Huimin Li, Ye Hu, Runjiu Fan, Tiankuo Chang, Xiangqian Zhuang, Long Yang, Zhibo Southern Univ Sci & Technol Sch Syst Design & Intelligent Mfg SDIM Shenzhen 518055 Peoples R China Zhengzhou Univ Sch Cyberspace Secur Zhengzhou 10459 Peoples R China Jilin Jianzhu Univ Sch Architecture & Planning Changchun 130118 Peoples R China Henan Univ Engn Sch Elect & Informat Engn Zhengzhou 11517 Peoples R China Univ Malaya Sch Dept Biomed Engn Kuala Lumpur 50603 Malaysia Anhui Univ Sch Integrated Circuits Hefei 230039 Peoples R China Xi An Jiao Tong Univ Natl Key Lab Aerosp Power Syst & Plasma Technol Xian 710049 Peoples R China Xi An Jiao Tong Univ Sch Mech Engn Xian 710049 Peoples R China

Composite plates are susceptible to various damages in complex conditions and working environments, which may reduce the reliability of the structure and threaten equipment and personal safety. Thus, the implementation of a robust online Structural health monitoring (SHM) system for these composite structures becomes imperative. To enhance reliability and safety, we introduce a robust online SHM system anchored by our newly developed damage detection Bayesian neural network (DD-BNN). The main contribution of this study lies in the DD-BNN to perform precise and reliable damage detection and localization in composite plates using only one actuator-receiver pair without any signal/feature pre-processing and human intervention. The proposed DD-BNN model innovatively combines probabilistic modeling with deep learning to address uncertainty in Lamb wave-based damage detection and model performance for composite plates, featuring a specialized probabilistic layer trained through Bayesian inference to efficiently encapsulate and manage uncertainty in model weights and activation. Notably, our method significantly simplifies the SHM system design and manual operation requirements. In addition, this approach not only reduces overfitting but also enhances robustness to noise, as confirmed by experiments on perturbation analysis of Gaussian and Poisson noise.

关键词： Composite plates Structural health monitoring Damage detection Lamb waves Bayesian neural network Deep learning

来源：评论

学校读者我要写书评

暂无评论

Stability analysis on state-dependent impulsive Hopfield neural networks via fixed-time impulsive comparison system method

引用

NEUROCOMPUTING 2018年 316卷 20-29页

作者： Zhou, Yinghua Li, Chuandong Wang, Hui Southwest Univ Coll Elect & Informat Engn Key Lab Nonlinear Circuits & Intelligent Informat Chongqing 400715 Peoples R China Chongqing Normal Univ Dept Math Chongqing 401331 Peoples R China

This paper aims at the stability problem of state-dependent impulsive Hopfield neural networks. Under well-selected conditions, we transform the considered neural networks into the analog with fixed-time impulses, namely, fixed-time impulsive comparison systems. By means of the stability theory of fixed-time impulsive systems, we establish several sufficient conditions for the exponential stability of state-dependent impulsive Hopfield neural networks. The present results show that state-dependent impulsive Hopfield neural networks can remain stability property of continuous subsystem even if the impulses are of somewhat destabilizing, and that stabilizing impulses can stabilize the unstable continuous subsystem. We illustrate the validity of the theoretical results by three numerical examples. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Hopfield neural networks (HNN) State-dependent impulse Comparison system method Exponential stability

来源：评论

学校读者我要写书评

暂无评论

P-Doped Carbon Quantum Dots with Antibacterial Activity

引用

MICROMACHINES 2021年第9期12卷 1116-1116页

作者： Chai, Shuiqin Zhou, Lijia Pei, Shuchen Zhu, Zhiyuan Chen, Bin Chongqing Univ Sci & Technol Chongqing Key Lab Ind Fermentat Microorganism 20 East Daxuecheng Rd Chongqing 401331 Peoples R China Chongqing Univ Sci & Technol Coll Chem & Chem Engn 20 East Daxuecheng Rd Chongqing 401331 Peoples R China Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuit & Intelligent Chongqing 400715 Peoples R China Zhejiang Univ Ocean Coll Hangzhou 316021 Peoples R China

It is a major challenge to effectively inhibit microbial pathogens in the treatment of infectious diseases. Research on the application of nanomaterials as antibacterial agents has evidenced their great potential for the remedy of infectious disease. Among these nanomaterials, carbon quantum dots (CQDs) have attracted much attention owing to their unique optical properties and high biosafety. In this work, P-doped CQDs were prepared by simple hydrothermal treatment of m-aminophenol and phosphoric acid with fluorescence emission at 501 nm when excited at 429 nm. The P-doped CQDs showed effective antibacterial activity against Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus). The minimal inhibitory concentrations (MICs) of P-doped CQD were 1.23 mg/mL for E. coli and 1.44 mg/mL for S. aureus. Furthermore, the morphologies of E. coli cells were damaged and S. aureus became irregular when treated with the P-doped CQDs. The results of zeta potential analysis demonstrated that the P-doped CQDs inhibit antibacterial activity and destroy the structure of bacteria by electronic interaction. In combination, the results of this study indicate that the as-prepared P-doped CQDs can be a promising candidate for the treatment of bacterial infections.

关键词： carbon quantum dots biocompatibility antibacterial activity

来源：评论

学校读者我要写书评

暂无评论

Distributed Energy Management Strategy for Reaching Cost-Driven Optimal Operation Integrated With Wind Forecasting in Multimicrogrids System

引用

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2019年第8期49卷 1643-1651页

作者： He, Xing Fang, Xinxin Yu, Junzhi Southwest Univ Chongqing Key Lab Nonlinear Circuits & Intelligen Sch Elect & Informat Engn Chongqing 400715 Peoples R China Chongqing Univ Sch Elect Engn Chongqing 400044 Peoples R China Peking Univ Dept Mech & Engn Sci Coll Engn State Key Lab Turbulence & Complex SystBIC ESAT Beijing 100871 Peoples R China

This paper considers the cost-driven optimal energy management strategy under a complex environment, multimicrogrids system. To provide the flexibility of load in depth, the heating, ventilating, and air conditioning (HVAC) load is investigated and explicitly formulated incorporated with indoor temperature dynamic function. The operation cost of wind generation includes the basic cost and additional cost to deal with the uncertainty of wind generation, which provides the trade-off between optimality and possibility. Furthermore, the energy management problem of multimicrogrid is presented according to different characteristics of generation devices, storage devices, and load. A distributed neurodynamic algorithm is presented to solve the nonsmooth optimization of energy management of multimicrogrids system. By this method, the only information exchanged among microgrids is the intermediate variable when computing. The simulation results validate the effectiveness of the proposed cost-driven energy management strategy.

关键词： Artificial neural network distributed energy management strategy heating ventilating and air conditioning (HVAC) multimicrogrids neurodynamic algorithm

来源：评论

学校读者我要写书评

暂无评论

An image segmentation algorithm based on double-layer pulse-coupled neural network model for kiwifruit detection

引用

COMPUTERS & ELECTRICAL ENGINEERING 2019年 79卷 106466-000页

作者： He, Fuliang Fu, Chunyun Shao, Huanzhe Teng, Jianqiao Southwest Univ Chongqing Key Lab Nonlinear Circuits & Intelligen Chongqing 400715 Peoples R China Southwest Univ Coll Elect & Informat Engn Chongqing 400715 Peoples R China Chongqing Univ Sch Automot Engn State Key Lab Mech Transmiss Chongqing 400044 Peoples R China Southwest Univ Westa Coll Chongqing 400715 Peoples R China

Finding a universal and accurate image segmentation algorithm for kiwifruit detection under varying illumination and complex background has become one of the most challenging problems in machine vision research. In this study, a robust segmentation algorithm based on a double-layer pulse-coupled neural network (PCNN) model is proposed. First of all, an improved PCNN merged with the image frequency-tuned saliency is devised as a basic structure. Secondly, in the red-green-blue color mode, the optimal color-difference information of a kiwifruit image is determined in the first layer of this double-layer PCNN. Then, enhanced hue features are fused with these optimal color-difference features by the total variation model. Finally, the target regions are built by the re-segmentation of the second layer of this double-layer PCNN. Experimental results demonstrate that the proposed algorithm significantly outperforms the typical existing algorithms in terms of the subjective visual effect and the objective quantitative evaluation. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Image segmentation Pulse-coupled neural network Frequency-tuned saliency Total variation model Kiwifruit recognition

来源：评论

学校读者我要写书评

暂无评论

A hybrid scheme for self-adaptive double color-image encryption

引用

MULTIMEDIA TOOLS AND APPLICATIONS 2018年第11期77卷 14285-14304页

作者： Han, Fang Liao, Xiaofeng Yang, Bo Zhang, Yushu Southwest Univ Chongqing Key Lab Nonlinear Circuits & Intelligen Coll Elect & Informat Engn Chongqing 400715 Peoples R China

Most of existing optical color image encryption schemes have born security risks due to the adoption of linear transform, and data redundancy for the generation of complex image. To settle these problems effectively, a hybrid scheme for self-adaptive double color-image encryption is proposed in this paper. In this scheme, each RGB color component of two secret color images is first compressed and encrypted by 2-D compressive sensing (CS) in which measurement matrices are generated by 1-D compound chaotic systems and further are optimized by steepest descent algorithm to improve image reconstruction effect. Then, the two measured images are regarded as the real part and imaginary part to constitute a complex image, respectively. In the end, the complex image is reencrypted by self-adaptive random phase encoding and discrete fractional random transform (DFrRT) to obtain the final encrypted data. In the process of DFrRT and random phase encoding, the correlations between R, G, B components are adequately utilized. The production of key streams not only depends on the initial values of chaotic systems but also on plaintexts, and the three color components affect each other to enhance the ability against the known plaintext attack. The projection neural network algorithm is adopted to obtain the decryption images. Simulation results also verify the validity and security of the proposed method.

关键词： Self-adaptive Compressive sensing Fractional random transform Image encryption Compound chaotic systems

来源：评论

学校读者我要写书评

暂无评论

Neural network optimization for energy-optimal cooperative computing in wireless communication system

引用

AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS 2018年 93卷 216-223页

作者： He, Yachen He, Xing Wang, Tiancai Southwest Univ Chongqing Key Lab Nonlinear Circuits & Intelligen Coll Elect & Informat Engn Chongqing 400715 Peoples R China

Thanks to the rapidly development of optimization algorithm, more energy can be saved in the communication system when executing an application. In recent years, allocating limited resources in a cooperative manner to maximize energy efficiency in emerging sensor networks has attracted a lot of attention. In this paper, a one layer projection neural network subject to linear equalities and bound constraints is introduced and applied in mobile wireless sensor network to make it energy-efficient by reasonably allocating local and remote data sizes when processing an application within a certain period of time. Firstly, an optimal partition to minimize the total energy consumption of the local and helper sensor nodes is proposed. Then, the neural network model is described and the optimality and convergence of the proposed model are analyzed. Finally, some simulation results are given to show that the proposed algorithm is very effective to solve the energy efficient cooperative computing.

关键词： Cooperative Energy efficient Mobile wireless sensor network Projection neural network

来源：评论

学校读者我要写书评

暂无评论

Cryptanalysis and enhancements of image encryption based on three-dimensional bit matrix permutation

引用

SIGNAL PROCESSING 2018年 142卷 292-300页

作者： Wu, Jiahui Liao, Xiaofeng Yang, Bo Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligen Chongqing 400715 Peoples R China

Recently, an image encryption based on three-dimensional bit matrix permutation (TDBMP) has been proposed by Zhang et al. The encryption scheme has combined Chen chaotic system with a 3D Cat map in the permutation stage, and defined a new mapping rule (double random position permutation) and utilized key-streams generated by Logistic map to confuse the permuted image. However, we have found that this scheme is vulnerable to chosen plaintext attack and is not applicable to secure communications. In this paper, the shortcomings of TDBMP have been analysed and a chosen plaintext attack has been proposed to break the scheme. After that, we propose an enhanced algorithm to overcome the presented shortcomings in the above original scheme. Experimental results also illustrate that the enhanced scheme not only maintains the merits of the original one, but also has better cryptographic performances in key space, plaintext sensitivity, statistical characteristics, robustness against cropping attack and execution speed, and can therefore effectively ensure a secure image communication. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Chaos Three-dimensional Chen system Three-dimensional cat map Permutation Confusion Cryptanalysis

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：