基于K-近邻法的局部加权朴素贝叶斯分类算法

分类算法一直以来都是数据挖掘领域的研究重点,朴素贝叶斯分类算法是众多优秀分类算法之一,但由于其条件属性必需独立,使得该算法也存在着一定的局限性。为了从另外一种角度来改进该算法,提高分类性能,提出了一种基于K-近邻法的局部加权朴素贝叶斯分类算法。使用K-近邻法对属性加权,找到最合适的加权值,运用加权后的朴素贝叶斯分类算法去分类,实验表明该算法提高了分类的可靠性与准确率。     

Stable local dimensionality reduction approaches

Dimensionality reduction is a big challenge in many areas. A large number of local approaches, stemming from statistics or geometry, have been developed. However, in practice these local approaches are often in lack of robustness, since in contrast to maximum variance unfolding (MVU), which explicitly unfolds the manifold, they merely characterize local geometry structure. Moreover, the eigenproblems that they encounter, are hard to solve. We propose a unified framework that explicitly unfolds the manifold and reformulate local approaches as the semi-definite programs instead of the above-mentioned eigenproblems. Three well-known algorithms, locally linear embedding (LLE), laplacian eigenmaps (LE) and local tangent space alignment (LTSA) are reinterpreted and improved within this framework. Several experiments are presented to demonstrate the potential of our framework and the improvements of these local algorithms.     

光滑分段孪生支持向量机

为了解决Sigmoid的积分函数对正号函数的逼近精度低的问题,引入一种具有更强逼近正号函数能力的光滑函数即分段函数,提出了光滑分段孪生支持向量机,并用快速Newton-Armijo算法对其求解.在NDC和UCI数据集上的实验结果表明:光滑分段孪生支持向量机能够有效地处理大规模和高维度数据,且分类精度和分类速度与光滑孪生支持向量机相比得到了改进.     

变体飞行器平滑切换LPV 鲁棒控制

针对一类变体飞行器控制问题, 提出一种平滑切换线性变参数(LPV) 鲁棒控制器设计方法. 建立变体飞行器切换LPV 模型, 设计平滑切换控制器, 其中偶数子系统控制器由相邻两个子系统控制器线性插值得到. 给出保证切换LPV 系统指数稳定且具有一定鲁棒性能的充分条件, 由于考虑了调参变量的渐变特性, 所得切换律没有平均驻留时间的限制. 仿真结果表明, 所提出方法使得飞行器系统既具有良好的稳定性和鲁棒性, 又能实现平滑切换.

     

基于ESO的一类线性时变系统自学习滑模控制方法

针对一类线性时变系统的控制问题,提出了一种基于扩张状态观测器的自学习滑模控制方法。该方法首先设计了两种非线性光滑函数, 然后将两种光滑函数分别应用于扩张状态观测器和滑模趋近律的设计。为了进一步提高系统的自适应控制能力, 使用最速下降法对滑模控制器的增益参数进行自学习镇定。仿真结果表明了该控制方法不仅响应速度快、控制精度高, 而且有效解决了现有理论方法难以解决的问题, 因而是一种有效的不依赖于被控对象模型的LTV系统控制方法。     

Adaptive fuzzy control with smooth inverse for nonlinear systems preceded by non-symmetric dead-zone

In this study, the adaptive output feedback control problem of a class of nonlinear systems preceded by non-symmetric dead-zone is considered. To cope with the possible control signal chattering phenomenon which is caused by non-smooth dead-zone inverse, a new smooth inverse is proposed for non-symmetric dead-zone compensation. For the systematic design procedure of the adaptive fuzzy control algorithm, we combine the backstepping technique and small-gain approach. The Takagi–Sugeno fuzzy logic systems are used to approximate unknown system nonlinearities. The closed-loop stability is studied by using small gain theorem and the closed-loop system is proved to be semi-globally uniformly ultimately bounded. Simulation results indicate that, compared to the algorithm with the non-smooth inverse, the proposed control strategy can achieve better tracking performance and the chattering phenomenon can be avoided effectively.