An efficient approach for face recognition based on common eigenvalues

In this paper, a simple technique is proposed for face recognition among many human faces. It is based on the polynomial coefficients, covariance matrix and algorithm on common eigenvalues. The main advantage of the proposed approach is that the identification of similarity between human faces is carried out without computing actual eigenvalues and eigenvectors. A symmetric matrix is calculated using the polynomial coefficients-based companion matrices of two compared images. The nullity of a calculated symmetric matrix is used as similarity measure for face recognition. The value of nullity is very small for dissimilar images and distinctly large for similar face images. The feasibility of the propose approach is demonstrated on three face databases, i.e., the ORL database, the Yale database B and the FERET database. Experimental results have shown the effectiveness of the proposed approach for feature extraction and classification of the face images having large variation in pose and illumination.     

Adaptive tracking control of an autonomous underwater vehicle

This paper presents the trajectory tracking control of an autonomous underwater vehicle(AUV). To cope with parametric uncertainties owing to the hydrodynamic effect, an adaptive control law is developed for the AUV to track the desired trajectory. This desired state-dependent regressor matrix-based controller provides consistent results under hydrodynamic parametric uncertainties.Stability of the developed controller is verified using the Lyapunov s direct method. Numerical simulations are carried out to study the efficacy of the proposed adaptive controller.     

基于时滞分割法的区间变时滞不确定系统鲁棒稳定新判据

针对一类存在泛数有界不确性的区间变时滞线性系统, 利用Lyapunov-Krasovskii (L-K) 泛函方法并结合线性矩阵不等式(LMI) 技术建立一种新的保守性更低的鲁棒稳定性判据. 首先基于时滞分割方法将时滞区间均分成N 等分, 针对不同的子区间构造合适的L-K 泛函; 然后在各自的分割区间采用保守性较小的积分不等式处理泛函沿时间的导数, 基于凸组合技术建立了LMI 形式的时滞相关稳定性新判据; 最后通过数值实例验证了结论的有效性.

     

一种改进型离散Hopfield学习算法

针对离散Hopfield 神经网络(DHNN) 的权值设计问题, 提出一种改进型学习算法, 并在DHNN动力学分析的基础上设计该学习算法. 利用矩阵分解的方法(MD) 得到正交矩阵, 并采用得到的正交矩阵直接计算DHNN的权值矩阵. 通过该学习算法得到的权值矩阵, 可以很好地存储训练样本的信息, 使测试样本收敛到稳定点. 该学习算法不需要进行分块计算, 减少了计算步骤和计算量, 降低了网络的迭代次数, 从而提高了网络运行速度. 最后, 将该学习算法应用于水质评价, 验证了其有效性和可行性.     

Bezier曲线到AH-Bezier曲线的升阶算法

关于曲线升阶,已有的结论往往限于同类曲线之间。为了突破这一限制,考虑不同类曲线间的升阶,关注代数多项式空间中的Bezier曲线到代数双曲多项式空间中的AH-Bezier曲线的升阶。研究从基函数入手,利用Bezier和AH-Bezier共有的求导降阶的特点,结合矩阵分块的思想,先给出AH-Bezier基到Bernstein基的转换矩阵,进而推出控制顶点的升阶公式,最后给出升阶算法。结果表明,任意n次Bezier曲线可以通过该算法升到n＋3阶（等同于n＋2次）的AH-Bezier曲线。算法实现了Bezier到AH-B＆#233;zier曲线模型的精确转换。     

具有椭圆盘极点约束的线性系统滤波器设计

针对一类线性系统,研究其闭环系统极点具有椭圆盘约束的情况下滤波器设计问题。在极点约束的前提下,控制目标要求闭环系统渐近稳定,并且干扰抑制性能指标小于给定的上界。首先利用有界实引理给出椭圆盘极点约束前提下滤波器的存在条件;其次,利用线性矩阵不等式技术,将滤波器的存在性问题转化成一组线性矩阵不等式(LMI)的可行性问题,根据LMI的可行解,给出滤波器的设计方法,由该方法得到的滤波器满足给定的性能要求;最后,数值算例说明该方法的有效性和可行性。     

Asynchronous fault detection filter design approach for discrete‐time switched linear systems

This paper is concerned with the problem of the fault detection filter design for discrete‐time switched linear systems with average dwell‐time. The designed fault detection filters are also switched systems, which are assumed to be asynchronously switched with the original switched systems. Improved results on the weighted l₂ performance and the H _? performance are first given, and the multiple Lyaounov‐like functions during matched period and unmatched period for the running time of one subsystem are used. By the aid of multiple Lyapunov‐like functions combined with Projection Lemma, the FD filters are designed such that the augmented systems under asynchronous switching are exponentially stable, and the residual signal generated by the filters achieves the weighted l₂‐gain for disturbances and guarantees the H _? performance for faults. Sufficient conditions are formulated by linear matrix inequalities, and the filter gains are characterized in terms of the solution of a convex optimization problem. Finally, examples are provided to demonstrate the effectiveness of the proposed design method. Copyright © 2012 John Wiley & Sons, Ltd.     

A generalized robust H ∞ filtering for singular Markovian jump systems and its applications

In this paper, a generalized robust H _∞ filtering method is proposed for a class of singular Markovian jump systems, whose generality is mainly embodied that the desired filter could bear perturbances in terms of uncertainties on its parameter matrices. Firstly, an LMI condition of robust mode‐dependent filter is developed. Based on the given result, a new approach to mode‐independent H _∞ filter is presented, which establishes a direct connection between mode‐dependent and mode‐independent filters. Secondly, when the transition rate matrix is with elementwise bounded uncertainties or partially unknown, sufficient conditions of such robust mode‐dependent and mode‐independent filters are all developed within LMI frameworks. Finally, a numerical example is used to demonstrate the effectiveness of the proposed methods. Copyright © 2013 John Wiley & Sons, Ltd.     

Observer‐based H ∞ control for networked systems with bounded random delays and consecutive packet dropouts

This paper is concerned with the H _∞ control problem for a class of systems with bounded random delays and consecutive packet dropouts that exist in both sensor‐to‐controller channel and controller‐to‐actuator channel during data transmission. A new model is developed to describe possible random delays and packet dropouts by two groups of Bernoulli distributed stochastic variables. To avoid the state augmentation, a full‐order observer‐based feedback controller is designed via LMI approach. Based on the Lyapunov theory, a sufficient condition is provided to guarantee the closed‐loop networked system to be asymptotically mean‐square stable and achieve the prescribed H _∞ disturbance‐rejection‐attenuation level. The simulation examples illustrate the effectiveness of the proposed method. Copyright © 2013 John Wiley & Sons, Ltd.