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Direct adaptive neural control for stabilization of nonlinear time-delay systems

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Science china(information Sciences) 2010年第4期53卷 800-812页

作者： WANG Min1,2., ZHANG SiYing2. CHEN Bing2.& LUO Fei2.1College of Automation, South china {2. of Technology, guangzhou 510641, china 2.nstitute of Complexity Science, Qingdao {2., Qingdao 2.6071, china 1. College of Automation South China University of Technology Guangzhou 510641 China2. Institute of Complexity Science Qingdao University Qingdao 266071 China

This paper is concerned with the problem of adaptive neural control for uncertain nonlinear strict-feedback time-delay systems with unknown virtual control coefficients. Radial basis function (RBF) neural networks are employed to directly approximate unknown virtual control signals, and then the adaptive neural control law is constructed by Lyapunov-Krasovskii functionals and backstepping. In order to avoid encountering a large number of adaptive parameters when using RBF neural networks as function approximators, an unknown constant, instead of unknown neural weights themselves, is employed as the estimated parameter. This technique makes only one adaptive parameter tuned online, thus significantly alleviating the burdensome computation. Meanwhile, some continuous functions are introduced to overcome the design difficulty originating from the use of one adaptive parameter. The proposed adaptive control guarantees the boundedness of all the signals in the closed-loop system. Simulation studies are presented to illustrate the effectiveness of the scheme.

关键词： nonlinear time-delay systems neural control adaptive control backstepping

Perceptual video hashing robust against geometric distortions

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Science china(information Sciences) 2012年第7期55卷 1520-1527页

作者： XIANG ShiJun 1,4 ,YANG JianQuan 2.& HUANG JiWu 3 1 School of information Science and Technology,Jinan university,{2. 510632.china 2.Shenzhen Institutes of Advanced Technology,Chinese Academy of Sciences,Shenzhen 518055,china 3 School of information Science and Technology,Sun Yat-sen university,{2. 5102.5,china 4 State Key Laboratory of information Security,Institute of Software,Chinese Academy of Sciences,Beijing 100049,china 1. School of information Science and Technology Jinan University Guangzhou 510632 China4. State Key Laboratory of Information Security Institute of Software Chinese Academy of Sciences Beijing 100049 China2. Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China3. School of Information Science and Technology Sun Yat-sen University Guangzhou 510275 China

In this paper,we propose a robust perceptual hashing algorithm by using video luminance histogram in *** underlying robustness principles are based on three main aspects:1) Since the histogram is independent of position of a pixel,the algorithm is resistant to geometric deformations; 2. the hash is extracted from the spatial Gaussian-filtering low-frequency component for those common video processing operations such as noise corruption,low-pass filtering,lossy compression,etc.; 3) a temporal Gaussian-filtering operation is designed so that the hash is resistant to temporal desynchronization operations,such as frame rate change and *** a result,the hash function is robust to common geometric distortions and video processing *** results show that the proposed hashing strategy can provide satisfactory robustness and uniqueness.

关键词： video hashing geometric distortion histogram Gaussian filtering

Vector bundle constraint for particle swarm optimization and its application to active contour modeling

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Progress in Natural Science:Materials International 2007年第10期17卷 1220-1225页

作者： Zeng Delu, Zhou Zhiheng and Xie Shengli(College of Electronic and information Engineering, South{2. university of Technology, guangzhou 510641,{2.) College of Electronic and information Engineering South China University of Technology Guangzhou 510641 China

Active contour modeling (ACM) has been shown to be a powerful method in object boundary extraction. In this paper, a new ACM based on vector bundle constraint for particle swarm optimization (VBCPSO-ACM) is proposed. Different from the traditional particle swarm optimization (PSO), in the process of velocity update, a vector bundle is predefined for each particle and velocity update of the particle is restricted to its bundle. Applying this idea to ACM, control points on the contour are treated as particles in PSO and the evolution of the contour is driven by the particles. Meanwhile, global searching is shifted to local searching in ACM by decreasing the number of neighbors and inertia. In addition, the addition and deletion of particles on the active contour make this new model possible for representing the real boundaries more precisely. The proposed VBCPSO-ACM can avoid self-intersection during contour evolving and also extract inhomogeneous boundaries. The simulation results proved its great performance in performing contour extraction.

关键词： boundary extraction active contour modeling particle swarm optimization velocity update vector bundle.

The Algorithm of Intelligent Compensation in Flexible Material Processing

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武汉理工大学学报 2006年第S1期28卷 162-166页

作者： TANG Luxin,DENG Xiaohui,LIU Zhiyuan (School of information Engineering Guangdong university of Technology,{2. 510006,china) School of information Engineering Guangdong university of Technology Guangzhou 510006China

Flexible material is easy to be distorted in high speed sewing process,so it must be tracked in the process. In this paper,The mathematics model is established with computer visual measure and digital image process for distorted flexible material. By the means of optimizing initial iterative value,the distorted variable of two correlated subareas evaluated. The method based on improved steepest descent algorithm and simulation annealing algorithm is proposed. It has been proven that the evaluating the algorithm’s error and convergent speed by the method of numerical emulate is the effective approach.

关键词： distorted flexible material visual measurement correlated algorithm

维普期刊数据库

RBF neural network and active circles based algorithm for contours extraction

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Progress in Natural Science:Materials International 2007年第6期17卷 681-686页

作者： Zhou Zhiheng, Zeng Delu and Xie Shengli(College of Electronic & information Engineering, South{2. university of Technology, guangzhou 510640,{2.) College of Electronic and information Engineering South China University of Technology Guangzhou 510640 China

For the contours extraction from the images, active contour model and self-organizing map based approach are popular nowadays. But they are still confronted with the problems that the optimization of energy function will trap in local minimums and the contour evolutions greatly depend on the initial contour selection. Addressing to these problems, a contours extraction algorithm based on RBF neural network is proposed here. A series of circles with adaptive radius and center is firstly used to search image feature points that are scattered enough. After the feature points are clustered, a group of radial basis functions are constructed. Using the pixels’ intensities and gradients as the input vector, the final object contour can be obtained by the predicting ability of the neural network. The RBF neural network based algorithm is tested on three kinds of images, such as changing topology, complicated background, and blurring or noisy boundary. Simulation results show that the proposed algorithm performs contours extraction greatly.

关键词： contours extraction RBF neural network dynamic clustering.

Sparsity analysis of signals

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Progress in Natural Science:Materials International 2006年第8期16卷 879-884页

作者： HE Zhaoshui, XIE Shengli and FU Yuli (School of Electronics and information Engineering, South china {2. of Technology, guangzhou 510640, china) [a]School of Electronics and information Engineering South China University of Technology Guangzhou China

In this paper, the signals with generalized Gaussian distribution are considered. A mathematical formula is given to illustrate the sparsity of the signals. According to this formula, the measure of the Laplacian signal is 1, and Gaussian signal is 2. Given a signal, compared with Laplacian signal and Gaussian signal, we can intuitively know how sparse the signal is via its measure. Some examples demonstrate that, if there are no sufficient observed signals (e. g. only three observed signals), one can achieve underdetermined blind source separation (BSS) only for the sufficiently sparse source signals (e.g. much sparser than Laplacian signals) by the measure we defined.

关键词： generalized Gaussian distribution ICA BSS sparseness Iso-Probability-Density contour.

Power functions with low uniformity on odd characteristic finite fields

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Science china mathematics 2010年第8期53卷 1931-1940页

作者： ZHA ZhengBang 1,3 & WANG XueLi 2.1 School of Mathematical Sciences,Luoyang Normal university,Luoyang 47102.,china 2.School of Mathematical Sciences,South{2. Normal university,guangzhou 510631,china 3 State Key Laboratory of information Security,Graduate university of Chinese Academy of Sciences,Beijing 100049,china 1. School of Mathematical Sciences Luoyang Normal University Luoyang 471022 China3. State Key Laboratory of Information Security Graduate University of Chinese Academy of Sciences Beijing 100049 China2. School of Mathematical Sciences South China Normal University Guangzhou 510631 China

In this paper,we give some new low differential uniformity of some power functions defined on finite fields with odd *** corollaries of the uniformity,we obtain two families of almost perfect nonlinear functions in GF... 详细信息

关键词： almost perfect nonlinear function differential uniform function finite field

维普期刊数据库

A novel framework of multi-channel acoustic echo cancellation

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Progress in Natural Science:Materials International 2006年第9期16卷 983-987页

作者： HE Zhaoshui, XIE Shengli and FU Yuli (School of Electronics & information Engineering, South china {2. of Technology, guangzhou 510640, china) [a]School of Electronics & information Engineering South China University Guangzhou China

Conventionally, multi-channel acoustic echo cancellation (AEC) achieves the goal by estimating the impulse responses of the local room. However, generally, conventional AEC methods have no unique solutions. Due to the strong correlation of the input signals, conventional methods are with many disadvantages. To overcome this problem, a new framework is proposed in this paper based on SIMO (single input multiple output) blind deconvolution. Under the new framework, we achieve the goal by identifying the impulse responses of distant room and avoiding the disadvantages of the conventional methods.

关键词： SIMO blind deconvolution multi-channel acoustic echo cancellation impulse response.

Blind signal separation of underdetermined mixtures based on clustering algorithms on planes

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Progress in Natural Science:Materials International 2007年第6期17卷 670-674页

作者： Xie Shengli, Tan Beihai and Fu Yuli(School of Electronics & information Engineering, South china {2. of Technology, guangzhou 510640, china) [a]School of Electronics & information Engineering South China University of Technology Guangzhou China

Based on clustering method on planes, blind signal separation (BSS) of underdetermined mixtures with three observed signals is discussed. The condition of sufficient sparsity of the source signals is not necessary when clustering method on planes is used. In other words, it needs not that only one source signal plays the main role among others at one time. The proposed method uses normal line clustering of planes first. Then, the mixing matrix can be identified via deciding the intersection lines of the planes. This method is an effective implement of the new theory presented by Georgiev. Simulations illustrate accuracy and restoring capability of the method to estimate the mixing matrix.

关键词： underdetermined mixture sparse representation mixing matrix blind signal separation.