基于正则化技术的对支持向量机特征选择算法

对支持向量机(twin support vector machine,TWSVM)的优化思想源于基于广义特征值近似支持向量机(proxi mal SVMbased on generalized eigenvalues,GEPSVM),问题解归结为求解两个SVM型问题,因此,计算开销缩减到标准SVM的1/4.除了保留了GEPSVM优势外,在分类性能上TWSVM远优于GEPSVM,但仍需求解凸规划问题,并且,目前尚无有效的TWSVM的特征提取算法提出.首先,向TWSVM模型中引入正则项,提出了正则化TWSVM(RTWSVM).与TWSVM不同,RTWSVM保证了该问题为一个强凸规划问题.在此基础上,构造了TWSVM的特征提取算法(FRTWSVM).该分类器只需求解一个线性方程系统,无需任何凸规划软件包.在保证得到与TWSVM相当的分类性能以及较快的计算速度上,此方式还减少了输入空间的特征数.对于非线性问题,FRTWSVM可以减少核函数数目.     

基于过滤驱动的键盘鼠标插入授权系统

为保证ATM的信息安全,分析Windows上键盘和鼠标设备驱动的工作原理,设计并实现基于过滤驱动的键盘鼠标插入事件授权系统。该授权系统能准确捕捉USB和PS/2接口的键盘鼠标设备的插拔事件,保证新插入的设备在系统授权前处于禁用状态。测试结果表明,系统能在Windows XP和Windows 7操作系统上高效稳定地运行。     

基于数字图像处理的虚拟输入方法

针对当前嵌入式设备输入方法存在的高成本低体验问题,提出了一种运行于嵌入式系统中基于数字图像处理的虚拟输入方法.该方法利用嵌入式设备附加的摄像设备,对用户在虚拟键盘上的按键过程进行图像采集,通过角点识别和图像分割进行按键识别,以便通过采集到的图像定位出用户点击的目标按键,从而实现信息输入过程.通过实例验证了该方法的可行性...     

Time-varying sliding mode control for a class of uncertain MIMO nonlinear system subject to control input constraint

To solve the regulator problem of a class of uncertain MIMO nonlinear systems subject to control input constraint, three types of time-varying sliding mode control laws are proposed. The sliding surfaces pass the initial value of the system at the initial time, and are shifted/rotated towards the predetermined ones. The controller parameters are optimized by genetic algorithm (GA). Lyapunov method is adopted to prove the stability and robustness to the parameter uncertainties and external disturbance. By me...     

考虑输入饱和的离散最优积分滑模控制

针对含有匹配有界干扰的线性离散系统, 提出一类最优积分滑模控制算法. 在系统开环极点位于单位圆内(上) 的前提下, 考虑输入饱和, 可以实现系统状态的半全局稳定. 该算法是低增益反馈和积分滑模的有益结合, 通过低增益反馈使输入饱和得到满足, 通过滑模控制增强了系统对干扰的鲁棒性; 另外, 该算法可以使特定的性能指标达到最优, 使系统稳态误差达到??(??²) 的量级. 仿真结果验证了所提出算法的有效性.

     

A note on interval observer design for unknown input estimation

This paper addresses the problem of interval observer design for unknown input estimation in linear time-invariant systems. Although the problem of unknown input estimation has been widely studied in the literature, the design of joint state and unknown input observers has not been considered within a set-membership context. While conventional interval observers could be used to propagate with some additional conservatism, unknown inputs by considering them as disturbances, the proposed approach allows their estimation. Under the assumption that the measurement noise and the disturbances are bounded, lower and upper bounds for the unmeasured state and unknown inputs are computed. Numerical simulations are presented to show the efficiency of the proposed approach.     

Consideration of plant behaviour in optimal servo-compensator design

Where the most prevalent optimal servo-compensator formulations penalise the behaviour of an error system, this paper considers the problem of additionally penalising the actual states and inputs of the plant. Doing so has the advantage of enabling the penalty function to better resemble an economic cost. This is especially true of problems where control effort needs to be sensibly allocated across weakly redundant inputs or where one wishes to use penalties to soft-constrain certain states or inputs. It is shown that, although the resulting cost function grows unbounded as its horizon approaches infinity, it is possible to formulate an equivalent optimisation problem with a bounded cost. The resulting optimisation problem is similar to those in earlier studies but has an additional ‘correction term’ in the cost function, and a set of equality constraints that arise when there are redundant inputs. A numerical approach to solve the resulting optimisation problem is presented, followed by simulations on a micro–macro positioner that illustrate the benefits of the proposed servo-compensator design approach.     

Stabilisation and consensus of linear systems with multiple input delays by truncated pseudo-predictor feedback

This paper provides a new approach referred to as pseudo-predictor feedback (PPF) for stabilisation of linear systems with multiple input delays. Differently from the traditional predictor feedback which is from the model reduction appoint of view, the proposed PPF utilises the idea of prediction by generalising the corresponding results for linear systems with a single input delay to the case of multiple input delays. Since the PPF will generally lead to distributed controllers, a truncated pseudo-predictor feedback (TPPF) approach is established instead, which gives finite dimensional controllers. It is shown that the TPPF can compensate arbitrarily large yet bounded delays as long as the open-loop system is only polynomially unstable. The proposed TPPF approach is then used to solve the consensus problems for multi-agent systems characterised by linear systems with multiple input delays. Numerical examples show the effectiveness of the proposed approach.     

Design of an adaptive fuzzy sliding mode control for uncertain discrete-time nonlinear systems based on noisy measurements

This paper presents the design of an adaptive fuzzy sliding mode control (AFSMC) for uncertain discrete-time nonlinear dynamic systems. The dynamic systems are described by a discrete-time state equation with nonlinear uncertainties, and the uncertainties include the modelling errors and the external disturbances to be unknown but nonlinear with the bounded properties. The states are measured by the restriction of measurement sensors and the contamination with independent measurement noises. The nonlinear uncertainties are approximated by using the fuzzy IF-THEN rules based on the universal approximation theorem, and the approximation error is compensated by adding an adaptive complementary term to the proposed AFSMC. The fuzzy inference approach based on the extended single input rule modules is proposed to reduce the number of the fuzzy IF-THEN rules. The estimates for the un-measurable states and the adjustable parameters are obtained by using the weighted least squares estimator and its simplified one. It is proved that under some conditions the estimation errors will remain in the vicinity of zero as time increases, and the states are ultimately bounded subject to the proposed AFSMC. The effectiveness of the proposed method is indicated through the simulation experiment of a simple numerical system.     

Effects of auditory,haptic and visual feedback on performing gestures by gaze or by hand

Modern interaction techniques like non-intrusive gestures provide means for interacting with distant displays and smart objects without touching them. We were interested in the effects of feedback modality (auditory, haptic or visual) and its combined effect with input modality on user performance and experience in such interactions. Therefore, we conducted two exploratory experiments where numbers were entered, either by gaze or hand, using gestures composed of four stroke elements (up, down, left and right). In Experiment 1, a simple feedback was given on each stroke during the motor action of gesturing: an audible click, a haptic tap or a visual flash. In Experiment 2, a semantic feedback was given on the final gesture: the executed number was spoken, coded by haptic taps or shown as text. With simultaneous simple feedback in Experiment 1, performance with hand input was slower but more accurate than with gaze input. With semantic feedback in Experiment 2, however, hand input was only slower. Effects of feedback modality were of minor importance; nevertheless, semantic haptic feedback in Experiment 2 showed to be useless at least without extensive training. Error patterns differed between both input modes, but again not dependent on feedback modality. Taken together, the results show that in designing gestural systems, choosing a feedback modality can be given a low priority; it can be chosen according to the task, context and user preferences.