IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics最新文献_第2页

Optimization of neural networks using variable structure systems. 用变结构系统优化神经网络。

IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics Pub Date : 2012-12-01 Epub Date: 2012-05-28 DOI: 10.1109/TSMCB.2012.2197610

Seyed Alireza Mohseni, Ai Hui Tan

引用次数: 19

Robust adaptive control of MEMS triaxial gyroscope using fuzzy compensator. 基于模糊补偿的MEMS三轴陀螺仪鲁棒自适应控制。

IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics Pub Date : 2012-12-01 Epub Date: 2012-05-03 DOI: 10.1109/TSMCB.2012.2196039

Juntao Fei, Jian Zhou

{"title":"Robust adaptive control of MEMS triaxial gyroscope using fuzzy compensator.","authors":"Juntao Fei, Jian Zhou","doi":"10.1109/TSMCB.2012.2196039","DOIUrl":"https://doi.org/10.1109/TSMCB.2012.2196039","url":null,"abstract":"In this paper, a robust adaptive control strategy using a fuzzy compensator for MEMS triaxial gyroscope, which has system nonlinearities, including model uncertainties and external disturbances, is proposed. A fuzzy logic controller that could compensate for the model uncertainties and external disturbances is incorporated into the adaptive control scheme in the Lyapunov framework. The proposed adaptive fuzzy controller can guarantee the convergence and asymptotical stability of the closed-loop system. The proposed adaptive fuzzy control strategy does not depend on accurate mathematical models, which simplifies the design procedure. The innovative development of intelligent control methods incorporated with conventional control for the MEMS gyroscope is derived with the strict theoretical proof of the Lyapunov stability. Numerical simulations are investigated to verify the effectiveness of the proposed adaptive fuzzy control scheme and demonstrate the satisfactory tracking performance and robustness against model uncertainties and external disturbances compared with conventional adaptive control method.","PeriodicalId":55006,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TSMCB.2012.2196039","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"30608809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 154

An effective feature selection method via mutual information estimation. 一种基于互信息估计的有效特征选择方法。

IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics Pub Date : 2012-12-01 Epub Date: 2012-05-07 DOI: 10.1109/TSMCB.2012.2195000

Jian-Bo Yang, Chong-Jin Ong

引用次数: 45

H∞ model reduction of Takagi-Sugeno fuzzy stochastic systems. Takagi-Sugeno模糊随机系统的H∞模型约简。

IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics Pub Date : 2012-12-01 Epub Date: 2012-05-18 DOI: 10.1109/TSMCB.2012.2195723

Xiaojie Su, Ligang Wu, Peng Shi, Yong-Duan Song

引用次数: 138

Supervised latent linear Gaussian process latent variable model for dimensionality reduction. 监督隐线性高斯过程隐变量降维模型。

IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics Pub Date : 2012-12-01 Epub Date: 2012-05-17 DOI: 10.1109/TSMCB.2012.2196995

Xinwei Jiang, Junbin Gao, Tianjiang Wang, Lihong Zheng

{"title":"Supervised latent linear Gaussian process latent variable model for dimensionality reduction.","authors":"Xinwei Jiang, Junbin Gao, Tianjiang Wang, Lihong Zheng","doi":"10.1109/TSMCB.2012.2196995","DOIUrl":"https://doi.org/10.1109/TSMCB.2012.2196995","url":null,"abstract":"The Gaussian process (GP) latent variable model (GPLVM) has the capability of learning low-dimensional manifold from highly nonlinear data of high dimensionality. As an unsupervised dimensionality reduction (DR) algorithm, the GPLVM has been successfully applied in many areas. However, in its current setting, GPLVM is unable to use label information, which is available for many tasks; therefore, researchers proposed many kinds of extensions to the GPLVM in order to utilize extra information, among which the supervised GPLVM (SGPLVM) has shown better performance compared with other SGPLVM extensions. However, the SGPLVM suffers in its high computational complexity. Bearing in mind the issues of the complexity and the need of incorporating additionally available information, in this paper, we propose a novel SGPLVM, called supervised latent linear GPLVM (SLLGPLVM). Our approach is motivated by both SGPLVM and supervised probabilistic principal component analysis (SPPCA). The proposed SLLGPLVM can be viewed as an appropriate compromise between the SGPLVM and the SPPCA. Furthermore, it is also appropriate to interpret the SLLGPLVM as a semiparametric regression model for supervised DR by making use of the GP to model the unknown smooth link function. Complexity analysis and experiments show that the developed SLLGPLVM outperforms the SGPLVM not only in the computational complexity but also in its accuracy. We also compared the SLLGPLVM with two classical supervised classifiers, i.e., a GP classifier and a support vector machine, to illustrate the advantages of the proposed model.","PeriodicalId":55006,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TSMCB.2012.2196995","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"30641269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 32

Gait recognition across various walking speeds using higher order shape configuration based on a differential composition model. 基于微分组成模型的高阶形状配置在不同行走速度下的步态识别。

IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics Pub Date : 2012-12-01 Epub Date: 2012-05-28 DOI: 10.1109/TSMCB.2012.2197823

Worapan Kusakunniran, Qiang Wu, Jian Zhang, Hongdong Li

{"title":"Gait recognition across various walking speeds using higher order shape configuration based on a differential composition model.","authors":"Worapan Kusakunniran, Qiang Wu, Jian Zhang, Hongdong Li","doi":"10.1109/TSMCB.2012.2197823","DOIUrl":"https://doi.org/10.1109/TSMCB.2012.2197823","url":null,"abstract":"Gait has been known as an effective biometric feature to identify a person at a distance. However, variation of walking speeds may lead to significant changes to human walking patterns. It causes many difficulties for gait recognition. A comprehensive analysis has been carried out in this paper to identify such effects. Based on the analysis, Procrustes shape analysis is adopted for gait signature description and relevant similarity measurement. To tackle the challenges raised by speed change, this paper proposes a higher order shape configuration for gait shape description, which deliberately conserves discriminative information in the gait signatures and is still able to tolerate the varying walking speed. Instead of simply measuring the similarity between two gaits by treating them as two unified objects, a differential composition model (DCM) is constructed. The DCM differentiates the different effects caused by walking speed changes on various human body parts. In the meantime, it also balances well the different discriminabilities of each body part on the overall gait similarity measurements. In this model, the Fisher discriminant ratio is adopted to calculate weights for each body part. Comprehensive experiments based on widely adopted gait databases demonstrate that our proposed method is efficient for cross-speed gait recognition and outperforms other state-of-the-art methods.","PeriodicalId":55006,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TSMCB.2012.2197823","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39972270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 67

Adjustable model-based fusion method for multispectral and panchromatic images. 基于可调模型的多光谱与全色图像融合方法。

IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics Pub Date : 2012-12-01 Epub Date: 2012-06-20 DOI: 10.1109/TSMCB.2012.2198810

Liangpei Zhang, Huanfeng Shen, Wei Gong, Hongyan Zhang

{"title":"Adjustable model-based fusion method for multispectral and panchromatic images.","authors":"Liangpei Zhang, Huanfeng Shen, Wei Gong, Hongyan Zhang","doi":"10.1109/TSMCB.2012.2198810","DOIUrl":"https://doi.org/10.1109/TSMCB.2012.2198810","url":null,"abstract":"In this paper, an adjustable model-based image fusion method for multispectral (MS) and panchromatic (PAN) images is developed. The relationships of the desired high spatial resolution (HR) MS images to the observed low-spatial-resolution MS images and HR PAN image are formulated with image observation models. The maximum a posteriori framework is employed to describe the inverse problem of image fusion. By choosing particular probability density functions, the fused HR MS images are solved using a gradient descent algorithm. In particular, two functions are defined to adaptively determine most regularization parameters using the partially fused results at each iteration, retaining one parameter to adjust the tradeoff between the enhancement of spatial information and the maintenance of spectral information. The proposed method has been tested using QuickBird and IKONOS images and compared to several known fusion methods using quantitative evaluation indices. The experimental results verify the efficacy of this method.","PeriodicalId":55006,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TSMCB.2012.2198810","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"30721891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 126

Global bounded consensus of multiagent systems with nonidentical nodes and time delays. 具有非相同节点和时滞的多智能体系统的全局有界一致性。

IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics Pub Date : 2012-10-01 Epub Date: 2012-05-09 DOI: 10.1109/TSMCB.2012.2192428

Wei-Song Zhong, Guo-Ping Liu, Clive Thomas

引用次数: 55

Crowd motion partitioning in a scattered motion field. 分散运动场中的人群运动分割。

IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics Pub Date : 2012-10-01 Epub Date: 2012-05-02 DOI: 10.1109/TSMCB.2012.2192267

Si Wu, Hau San Wong

引用次数: 50

On prioritized multiple-criteria aggregation. 基于优先的多标准聚合。

IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics Pub Date : 2012-10-01 Epub Date: 2012-04-04 DOI: 10.1109/TSMCB.2012.2189560

Ronald R Yager

引用次数: 48