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111.
In order to conveniently analyze stability of uncertain multiple input-delayed closed-loop systems and successfully synthesize passive controllers for a general class of uncertain multiple input-delayed systems with disturbance, the so-called reduction method is applied to the multiple input-delayed systems with parametric uncertainties. A feedback controller associated with the system state and the past control action is designed to guarantee the passivity of the closed-loop systems for all admissible uncertainties. The theoretical findings are illustrated and verified with one numerical example. 相似文献
112.
陕晋军 《网络安全技术与应用》2010,(11):43-46
本文介绍了当前基于Struts2、Spring、Hibernate框架的高职院校成绩管理系统的分析和设计。 相似文献
113.
Gradient based and least-squares based iterative identification algorithms are developed for output error (OE) and output error moving average (OEMA) systems. Compared with recursive approaches, the proposed iterative algorithms use all the measured input–output data at each iterative computation (at each iteration), and thus can produce highly accurate parameter estimation. The basic idea of the iterative methods is to adopt the interactive estimation theory: the parameter estimates relying on unknown variables are computed by using the estimates of these unknown variables which are obtained from the preceding parameter estimates. The simulation results confirm theoretical findings. 相似文献
114.
This paper investigates the problem of robust exponential stability for neutral systems with time-varying delays and nonlinear perturbations. Based on a novel Lyapunov functional approach and linear matrix inequality technique, a new delay-dependent stability condition is derived. Since the model transformation and bounding techniques for cross terms are avoided, the criteria proposed in this paper are less conservative than some previous approaches by using the free-weighting matrices. One numerical example is presented to illustrate the effectiveness of the proposed results. 相似文献
115.
This paper provides the stochastic finite-time stabilization and H
∞ control problem of Markov jump systems with norm-bounded uncertainties and state delays that possess randomly jumping parameters.
The transition of the jumping parameters is governed by a finite-state Markov process. The finite-time H
∞ controller via state feedback is provided to guarantee the stochastic finite-time bounded-ness and stochastic finite-time
stabilization of the resulting closed-loop system for all admissible uncertainties and unknown time-delays. The control criterion
is formulated in the form of linear matrix inequalities and the designed finite-time stabilization controller is described
as an optimization one. Simulation results illustrate the effectiveness of the developed approaches. 相似文献
116.
117.
Incremental Linear Discriminant Analysis Using Sufficient Spanning Sets and Its Applications 总被引:1,自引:0,他引:1
Tae-Kyun Kim Björn Stenger Josef Kittler Roberto Cipolla 《International Journal of Computer Vision》2011,91(2):216-232
This paper presents an incremental learning solution for Linear Discriminant Analysis (LDA) and its applications to object
recognition problems. We apply the sufficient spanning set approximation in three steps i.e. update for the total scatter matrix, between-class scatter matrix and the projected data
matrix, which leads an online solution which closely agrees with the batch solution in accuracy while significantly reducing
the computational complexity. The algorithm yields an efficient solution to incremental LDA even when the number of classes
as well as the set size is large. The incremental LDA method has been also shown useful for semi-supervised online learning.
Label propagation is done by integrating the incremental LDA into an EM framework. The method has been demonstrated in the
task of merging large datasets which were collected during MPEG standardization for face image retrieval, face authentication
using the BANCA dataset, and object categorisation using the Caltech101 dataset. 相似文献
118.
Jianli LiuAuthor Vitae Baoqi ZuoAuthor Vitae Xianyi ZengAuthor Vitae Philippe VromanAuthor Vitae Besoa RabenasoloAuthor Vitae 《Neurocomputing》2011,74(17):2813-2823
This work is dedicated to develop an algorithm for the visual quality recognition of nonwoven materials, in which image analysis and neural network are involved in feature extraction and pattern recognition stage, respectively. During the feature extraction stage, each image is decomposed into four levels using the 9-7 bi-orthogonal wavelet base. Then the wavelet coefficients in each subband are independently modeled by the generalized Gaussian density (GGD) model to calculate the scale and shape parameters with maximum likelihood (ML) estimator as texture features. While for the recognition stage, the robust Bayesian neural network is employed to classify the 625 nonwoven samples into five visual quality grades, i.e., 125 samples for each grade. Finally, we carry out the outlier detection of the training set using the outlier probability and select the most suitable model structure and parameters from 40 Bayesian neural networks using the Occam's razor. When 18 relevant textural features are extracted for each sample based on the GGD model, the average recognition accuracy of the test set arranges from 88% to 98.4% according to the different number of the hidden neurons in the Bayesian neural network. 相似文献
119.
核参数优化选取的混合C均值核模糊聚类算法 总被引:1,自引:0,他引:1
为了减小噪声点对聚类中心的影响,可能性聚类算法(PCM)把可能隶属关系引入到聚类的过程中,但是其往往趋向找到相同的集群。PFCM算法同时利用隶属度与可能性把数据点划分到不同的集群中,提高了算法的抗噪能力,但PFCM算法对发现大小不相等的集群并不十分理想。针对上述问题,提出了一种核参数优化选取的混合C均值核模糊聚类算法,该算法通过利用优化选取核参数的核函数把在原始空间中非线性可分的群体转化成高维空间中同质集群。实验结果表明,该算法能更好地发现融入噪音数据集的聚类中心,获得数据集质量更好的划分。 相似文献
120.
基于几何不变量的直线匹配方法 总被引:1,自引:1,他引:0
针对目前直线匹配算法大多基于直线段支持区域的几何特性、灰度特性,但这些特性又极易受外界因素干扰造成匹配失败的情况,提出了基于直线几何不变量的匹配方法,该方法在无任何已知条件的情况下,运用叉积符号、点的线束交比不变量进行直线匹配。对于各个视点图像,采用Hough变换提取直线间交点集,再采用Graham扫描法构造一个最小的凸包,并通过匹配凸包顶点的交比序列来建立点与点的对应关系,选取其中一个对应关系完成直线的匹配。实验结果表明,该方法鲁棒性较好,具有广泛的应用性。 相似文献