检索结果-内蒙古大学图书馆

12th International Conference on information Science and Technology, ICIST 2022

作者： Che, Hangjun Wang, Jun Cichocki, Andrzej College of Electronic and Information Engineering Southwest University Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Chongqing400715 China City University of Hong Kong Department of Computer Science and School of Data Science Hong Kong Hong Kong Skolkovo Institute of Science and Technology Moscow143026 Russia

ISBN: (数字)9781665485821

ISBN: (纸本)9781665485821

In this paper, sparse signal reconstruction is for-mulated a q-ratio minimization problem subjecting to linear underdetermined equations. In view of the nonconvexity of the objective function, the q-ratio formulation with q=2 is approximately reformulated as an iteratively reweighted convex optimization problem in the majorization-minimization frame-work. A neurodynamic optimization approach is introduced to solve the formulated problem iteratively. The experimental results on sparse signal reconstruction are discussed to demonstrate the performance of the proposed approach. © 2022 IEEE.

关键词： Convex optimization

来源：评论

学校读者我要写书评

暂无评论

A Multi-Kernel-Based Multi-View Deep Non-Negative Matrix Factorization for Enhanced Healthcare Data Clustering

引用

IEEE Transactions on Consumer Electronics 2024年 1-1页

作者： Che, Hangjun Yang, Xuanhao College of Electronic and Information Engineering Southwest University and Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Chongqing China College of Electronic and Information Engineering Southwest University Chongqing China

Multi-view clustering methods based on deep matrix factorization play a vital role in data analysis within the healthcare sector. However, existing methods predominantly conduct deep matrix factorization in the original data space, which is not conducive to addressing non-linear and complex data patterns. To address this issue, the Multi-kernel based Multi-view Deep Non-negative Matrix Factorization with Optimal Consensus Graph (OGMKMDNMF) is introduced. This approach utilizes deep non-negative matrix factorization after projecting the data matrix into a high-dimensional kernel space. Additionally, it employs optimal consensus graph to alleviate the detrimental effects arising from misassigned nearest neighbors during the construction of similarity matrix. An innovative iterative optimization algorithm is developed for OGMKMDNMF. The experimental results demonstrate the effectiveness and competitive advantage of OGMKMDNMF in addressing multi-view healthcare data clustering tasks. IEEE

关键词： Cluster analysis

来源：评论

学校读者我要写书评

暂无评论

Stress recognition based on graph structure representation of facial StO2

Stress recognition based on graph structure representation o...

引用

2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Wang, Jiaxiu Liu, Xinyu Jia, Yingjuan Chen, Tong Huang, Jingru Zhang, Zheyuan Southwest University College of Electronic and Information Engineering Chongqing400715 China Southwest University Institute of Legal Psychology and Intelligent Computing Chongqing400715 China Southwest University Chongqing Key Laboratory of Non-Linear Circuits and Intelligent Information Processing Chongqing400715 China

ISBN: (纸本)9798350337488

Stress is an integral state that affects physical and mental health of individuals. Tissue Oxygen Saturation (StO2) is an emerging physiological signal and can reflect different stress states. Previous studies have simply extracted features of StO2 from specific regions of the face without exploring potential associations between them. In this paper, we analyze the facial Region of Interest (ROI) based on StO2, so as to explore the deep relationship between ROIs. Building upon this, we construct, for the first time, a StO2-based facial graph structure for stress recognition by using ROIs as nodes. In addition, we propose a new graph pooling method called FTPool which allows to measure node significance in terms of both node characteristics and graph topology. Finally, we further propose a dual-stream network (GCNet) combining GNN and CNN for the baseline-independent stress recognition. The experimental results show that the proposed GCNet can achieve state-of-the-art (SOTA) results with an accuracy of 78.57% on the original unbalanced database. © 2023 IEEE.

关键词： Graph pooling Graph structure Regions of Interest Stress recognition Tissue oxygen saturation

来源：评论

学校读者我要写书评

暂无评论

An Image Denoising Method Based on Deep Residual GAN 4

An Image Denoising Method Based on Deep Residual GAN

引用

2020 4th International Workshop on Advanced Algorithms and Control Engineering, IWAACE 2020

作者： Wang, Ziyuan Wang, Lidan Duan, Shukai Li, Yunfei Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Chongqing400715 China Schoolof Electronic and Information Engineering Southwest University Chongqing400715 China College of Artificiall Intelligence Southwest University Chongqing400715 China Braininspired Computing and Intelligent Control of Chongqing Key Lab Chongqing400715 China National and Local Joint Engineering Laboratory of Intelligent Transmission and Control Technology Chongqing400715 China Chongqing Brain Science Collaborative Innovation Center Chongqing400715 China

As people come into contact with image data more often, high quality and clear images attract more attention. Many methods have been proposed to deal with image noise problem including deep learning (DL). However most of them is lack of capability when customers want more perceptual details of the image without information loss. In this paper, a deep residual network based on generative adversarial (GAN) network was proposed to complete the image denoising mission. Firstly, a generative-adversarial network structure based on residual blocks was designed. Secondly, a refined loss function was given to train the GAN network. The well designed loss function can help the generated image to be very close to the clear counterpart (ground truth) while enhancing more details in colours and brightness. Finally, extensive experiments show that our network is not only convincing for images denoising, but also effective for other image process tasks, such as image defogging, medical CT denoising etc., presenting impressive and competitive effects. © Published under licence by IOP Publishing Ltd.

关键词： Image denoising

来源：评论

学校读者我要写书评

暂无评论

Association Rules Hiding via Multi-Objective Differential Evolution Algorithm

Association Rules Hiding via Multi-Objective Differential Ev...

引用

International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS)

作者： Nankun Mu Fan Yang Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Southwest University Chongqing P.R. China

ISBN: (数字)9781728158570

ISBN: (纸本)9781728158587

Association rules (ARs) mining has been widely used in discovering interesting patterns from massive data as a key data mining technique. However, this mining technique may lead to the disclosure of sensitive ARs, and thus, the ARs hiding strategy is very important and necessary. In this paper, a novel ARs hiding method (DEvoArH) is proposed for hiding the ARs. Noting that there are three side-effects in ARs hiding (ARH), i.e., the hiding failure rate, the lost rules rate, and the ghost rules rate, a multi-objective differential evolution algorithm is carefully designed. Specifically, the Pareto-optimal solutions are defined as the elite set, and then each solution is capable of learning from the elite set with a certain probability. Considering the convergence speed and search ability, a directional mutation and random mutate round is introduced into the mutation operator. Besides, to further decrease the data change rate, a database pre-processing mechanism is proposed to filter the unrelated data before the hiding process. Finally, the results of the comparison experiments also demonstrate the superiority of the proposed ARH method in terms of the three side-effects and efficiency.

关键词： association rules hiding multi-objective optimal evolutionary algorithm

来源：评论

学校读者我要写书评

暂无评论

Cooperative Hybrid VLC-RF Systems for WSNs

Cooperative Hybrid VLC-RF Systems for WSNs

引用

Asia-Pacific Signal and information processing Association Annual Summit and Conference (APSIPA)

作者： Chao Zhang Jia Ye Jia Shi Gaofeng Pan Zan Li Zhiguo Ding SWU Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Chongqing China State key laboratory of integrated services networks Xidian University Xi'an China

ISBN: (纸本)9781728102436;9789881476852

In this paper, a cooperative hybrid visible light communication (VLC)-radio frequency (RF) wireless sensor network, which includes a transmitter ( S) with a cluster of light emitting diodes (LED) lamps, a relay ( R) and a destination ( D), is taken into consideration. Specially, R is randomly located in the coverage of the LED lamps, D is randomly distributed out of the coverage of the LED lamps. Then, VLC is employed for S-R link and traditional radio frequency (RF) communication technology is adopted over R-D link. Moreover, both of decode-forward (DF) and amplify-forward (AF) relay schemes are considered at R to aid the data transmissions between S and D. Considering Nakagami- m fading over R-D link, and the randomness of the locations of R and D, the statistical characteristics of the received signal-to-noise ratio at D under both AF and DF relay schemes are characterized, respectively. After that, approximated analytical expressions for the outage probability of the considered system are respectively derived. Finally, simulation and numerical analysis are conducted to verify the correctness of our proposed analytical models.

关键词： Relays LED lamps Radio frequency Signal to noise ratio Wireless sensor networks Fading channels

来源：评论

学校读者我要写书评

暂无评论

Fixed-relative-switch strategies for learning based event-triggered control of nonlinear multiagent systems

arXiv

引用

arXiv 2024年

作者： Wang, Ziming Gao, Yun Rikos, Apostolos I. Wang, Xin Ji, Yiding Guangzhou China Guangzhou China The Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Southwest University Chongqing China

This paper investigates event-triggered control for consensus tracking in nonlinear semi-strict-feedback multi-agent systems (MASs) with unknown states and subject to disturbances. We begin by employing radial basis function neural networks combined with the backstepping method to approximate the unknown nonlinear dynamics of the MASs, which facilitates the development of state and disturbance observers for estimation. We then propose three adaptive event-triggered control strategies: fixed-threshold, relative-threshold, and switch-threshold, whose controllers and triggering conditions are defined acocrdingly. By applying Lyapunov stability theory, we rigorously prove that all follower agents’ outputs consistently track the reference of their leader, and all error signals remain uniformly bounded. Moreover, our control strategies effectively mitigate the occurrence of Zeno behaviors. To validate our control framework, an illustrative example is provided to demonstrate its desirable performance in consensus tracking and triggering efficiency. Copyright © 2024, The Authors. All rights reserved.

关键词： Radial basis function networks

来源：评论

学校读者我要写书评

暂无评论

Cross-Subject Emotion Recognition with a Decision Tree Classifier Based on Sequential Backward Selection

Cross-Subject Emotion Recognition with a Decision Tree Class...

引用

International Conference on intelligent Human-Machine Systems and Cybernetics, IHMSC

作者： Wenge Jiang Guangyuan Liu Xingcong Zhao Fu Yang School of Electronic and Information Engineering Southwest University Chongqing China Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Southwest University Chongqing China

Many of the current emotion recognitions are intra-subject, the reason is that recognize cross-subject emotions have always been difficult. In this paper, we proposed a decision tree classifier based on sequential backward selection (DT-SBS), and "leave-one-subject-out" verification strategy was used for evaluating performance of cross-subject emotion recognition. Power spectral density (PSD) was extracted from EEG signals as feature set. The emotion recognition performance of the method we proposed was examined on EEG data of a group of subjects. The pictures were utilized to stimulate the emotion of 12 subjects and we collected their EEG signals (PEEG), the mean recognition accuracy of 65.8%. The dataset for emotion analysis using physiological signals (DEAP) was utilized to verify the method we proposed in this paper and the mean recognition accuracy of 65.2%. Compared with the performance reported in the existing literature, the method we proposed in this paper was effective in cross-subject emotion recognition. In addition, the emotion recognition performance of different rhythms were explored, we found that the mean recognition accuracy of PSD in the gamma rhythm achieved the best mean recognition accuracy compared with the other rhythms; the high frequency bands contained higher emotional information than the low frequency bands.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Privacy-Preserving Fuzzy Multi-keyword Search for Multiple Data Owners in Cloud Computing

Privacy-Preserving Fuzzy Multi-Keyword Search for Multiple D...

引用

IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Lvhao Chen Xiaofeng Liao Nankun Mu Jiahui Wu Junqing Junqing Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Electronic and Information Engineering Southwest University Chongqing P.R. China Computer Science Chongqing University Chongqing P. R. China Le Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Electronic and Information Engineering Southwest University Chongqing P.R. China

ISBN: (数字)9781728124858

ISBN: (纸本)9781728124865

With cloud computing's development, more users are decide to store information on the cloud server. Owing to the cloud server's insecurity, many documents should be encrypted to avoid information leakage before being sent to the cloud. Nevertheless, it leads to the problem that plaintext search techniques can not be directly applied to the ciphertext search. In this case, many searchable encryption schemes based on single data owner model have been proposed. But, the actual situation is that users want to do research with encrypted documents originating from various data owners. This paper puts forward a privacy-preserving scheme that is based on fuzzy multi-keyword search (PPFMKS) for multiple data owners. For the sake of espousing fuzzy multi-keyword and accurate search, secure indexes on the basis of Locality-Sensitive Hashing (LSH) and Bloom Filter (BF)are established. To guarantee the search privacy under multiple data owners model, a new encryption method allowing that different data owners have diverse keys to encrypt files is proposed. This method also solves the high cost caused by inconvenience of key management.

关键词： Cloud computing Servers Indexes Encryption Data privacy

来源：评论

学校读者我要写书评

暂无评论

Event-Triggered Optimal Tracking Control for Strict-Feedback nonlinear Systems With Non-Affine nonlinear Faults

arXiv

引用

arXiv 2024年

作者： Wang, Ling Wang, Xin Wang, Ziming Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Southwest University Chongqing400044 China Guangzhou Nansha511458 China

This article studies the control ideas of the optimal backstepping technique, proposing an event-triggered optimal tracking control scheme for a class of strict-feedback nonlinear systems with non-affine and nonlinear faults. A simplified identifier-critic-actor framework is employed in the reinforcement learning algorithm to achieve optimal control. The identifier estimates the unknown dynamic functions, the critic evaluates the system performance, and the actor implements control actions, enabling modeling and control of anonymous systems for achieving optimal control performance. In this paper, a simplified reinforcement learning algorithm is designed by deriving update rules from the negative gradient of a simple positive function related to the Hamilton-Jacobi-Bellman equation, and it also releases the stringent persistent excitation condition. Then, a fault-tolerant control method is developed by applying filtered signals for controller design. Additionally, to address communication resource reduction, an event-triggered mechanism is employed for designing the actual controller. Finally, the proposed scheme’s feasibility is validated through theoretical analysis and simulation. Copyright © 2024, The Authors. All rights reserved.

关键词： Backstepping

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：