Algebraic criteria for positive realness relative to the unit circle

A purely algebraic algorithm is developed for testing positive real character of real rational functions and matrices relative to the unit circle in the complex plane. Since the algorithm is entirely recursive and is performed in a finite number of steps, it is suitable for machine computations.     

实代数数符号判定的一种新算法

根据多元多项式结式、笛卡尔符号法则、多项式实根隔离和实连续函数的性质等理论,给出对任意实代数数进行符号判定的一种新算法.测试实例表明,本文提出的算法还能有效地解决Maple系统中关于浮点数运算的一些缺陷.     

函数优化的模糊粒子群算法

在传统粒子群算法的基础上运用模糊规则表加入了新的扰动因子,提出了一种新的算法--模糊粒子群算法。算法结合了模糊控制器中输入输出的模糊化处理和粒子群寻优的特点,为实际问题提供了新的解决手段。将模糊粒子群算法应用于函数优化的问题上,通过多组实例数据进行测试,验证表明了本算法具有良好的有效性和鲁棒性。     

On the minimum-norm least squares solution of the complex generalized coupled sylvester matrix equations

By means of the real linear operator, we establish an iterative algorithm for solving a class of complex generalized coupled Sylvester matrix equations. The finite termination of the proposed algorithm is proved. By representing a complex matrix as a larger real matrix, we present a new method to prove that the minimum-norm solution or minimum-norm least squares solution of the complex generalized coupled Sylvester matrix equations can be obtained by an appropriate selection for the initial matrices, which has not been found in the existing work. Numerical experiments on some randomly generated data and practical image restoration problem show that the proposed algorithm is feasible and effective.     

The bootstrapping of the Yarowsky algorithm in real corpora

The Yarowsky bootstrapping algorithm resolves the homograph-level word sense disambiguation (WSD) problem, which is the sense granularity level required for real natural language processing (NLP) applications. At the same time it resolves the knowledge acquisition bottleneck problem affecting most WSD algorithms and can be easily applied to foreign language corpora. However, this paper shows that the Yarowsky algorithm is significantly less accurate when applied to domain fluctuating, real corpora. This paper also introduces a new bootstrapping methodology that performs much better when applied to these corpora. The accuracy achieved in non-domain fluctuating corpora is not reached due to inherent domain fluctuation ambiguities.     

An algorithmic approach for system decomposition and balanced realized model reduction

This paper deals with the development of an algorithm for unstable continuous/discrete-time system decomposition into completely stable and completely unstable subsystems using real Schur transformation technique. The application of the proposed algorithm is investigated for unstable LTI plant or controller reduction and the available balanced realized model reduction theories applicable for stable systems are extended for unstable, continuous/discrete-time systems. The algorithm and its applications are illustrated with MATLAB-based computer-simulated results for continuous and discrete-time systems.     

基于遗传算法的R＆D项目实物期权评价模型

为了有效地解决R&D项目评价中存在的多变量、多目标、多阶段、不确定性等复杂问题 ,本文提出了基于遗传算法的R&D项目实物期权评价模型和求解步骤     

基于插值预测的快速查找算法

针对二分法的不足,提出了一种基于拉格朗日插值的动态预测查找算法,并将该算法和二分法结合得到改进的插值预测查找算法。改进算法在最坏的情况下,在含有n个元素的有序数列中,查找一个元素的最大循环比较次数为1到[log2n]＋1之间,优于二分查找的[log2n]＋1,最后从理论上证明了这一结论,并在求解一元高次方程实数解的应用中验证了这一结论。     

Decentralized neural identification and control for uncertain nonlinear systems: Application to planar robot

This paper presents a discrete-time decentralized neural identification and control for large-scale uncertain nonlinear systems, which is developed using recurrent high order neural networks (RHONN); the neural network learning algorithm uses an extended Kalman filter (EKF). The discrete-time control law proposed is based on block control and sliding mode techniques. The control algorithm is first simulated, and then implemented in real time for a two degree of freedom (DOF) planar robot.     

Asymmetric Gaussian chirplet model and parameter estimation for generalized echo representation

Gaussian Chirplet Model (GCM) is commonly used for signal analysis in many fields including ultrasound, radar, sonar, seismology, and biomedicine. The symmetric envelope of GCM is often inadequate in representing real echo envelopes which are more likely to be asymmetric. In our previous work we introduced the Asymmetric Gaussian Chirplet Model (AGCM) that generalizes the GCM. In this paper, an efficient successive parameter estimation algorithm is proposed utilizing echo envelope and instantaneous phase obtained via analytical signal representation. The initial parameters obtained via successive estimation are fine-tuned with a fast Gauss–Newton algorithm developed for the AGCM to achieve Maximum Likelihood Estimation (MLE) of model parameters. The performance of parameter estimation algorithm is formally verified employing Monte-Carlo simulations and Cramer–Rao Lower Bounds. Parameter estimation is shown to be minimum variance and unbiased for SNR levels 10 dB and higher. Furthermore, AGCM has been tested on real ultrasound echoes measured from planar targets. AGCM provides better echo fits than the GCM due to its more flexible envelope.     

The relaxed gradient-based iterative algorithms for a class of generalized coupled Sylvester-conjugate matrix equations

In this paper, two relaxed gradient-based iterative algorithms for solving a class of generalized coupled Sylvester-conjugate matrix equations are proposed. The proposed algorithm is different from the gradient-based iterative algorithm and the modified gradient-based iterative algorithm that are recently available in the literature. With the real representation of a complex matrix as a tool, the sufficient and necessary condition for the convergence factor is determined to guarantee that the iterative solution given by the proposed algorithms converge to the exact solution for any initial matrices. Moreover, some sufficient convergence conditions for the suggested algorithms are presented. Finally, numerical example is provided to illustrate the effectiveness of the proposed algorithms and testify the conclusions suggested in this paper.     

基于脉冲积累的SAR实时聚焦算法

在实际的SAR场景中,由于载机平台运动的不规律会引入相位误差,这将导致SAR图像出现模糊,甚至不能形成图像,因此需要准确地估计和补偿相位误差.提出一种较好的SAR相位历史估计算法,在方位向应用延时自相关方法进行准确的相位估计,由此实现SAR的准确聚焦成像.该相位估计方法具有较高的计算效率,非常适合于实时SAR系统.利用对实际SAR数据的聚焦处理证明了该方法的有效性.     

基于小波变换的PET图像分析

提出一种把小波变换和统计检验结合起来检测PET图像激活区的方法.首先,采用模拟的PET图像来评价算法的可靠性,结果显示,在小波域上进行统计检验比传统的直接在空间域上进行统计检验具有更高的灵敏度,更强的抗噪声干扰性能,更快的计算速度.最后,用该方法处理真实的PET图像,也得到了满意的结果.该方法为PET医学图像处理和脑功能研究提供了一种新的多尺度、高性能的分析手段,对于脑功能研究的功能区定位、临床诊断、药物疗效评估等有着重要意义.     

最大流算法及其应用

本文介绍了图论中最大流问题的算法，并且讨论Ford—Fulkerson等算法在解决实际问题中的应用。     

基于分布式聚合RSS的文件传输技术研究

针对在无线网络中传输大规模数据时存在出错率高等问题,提出了一种基于改进型RSS算法的高效率文件传输算法。该技术基于分布式无线通信模式,服务器端建立基于Feed的分布式文件传输架构,通过协作通信的方式向客户端广播RSS更新消息,在无线文件传输控制信息的端到端时延和网络吞吐率上进行优化。实验表明所提出的技术与原RSS技术相比在无线文件传输的可靠性、实时性、资源利用率等方面具有良好的性能。     

改进的多传感器图像融合算法研究

多传感器图像融合是将不同传感器得到的多个图像,根据某个像素的对应位置进行叠加处理,以得到一个满足某种需求的新图像。本文采用一种冲突惩罚因子的多传感器图像融合算法,实时运用冲突惩罚因子,选取高信息量的像素进行平滑融合。仿真实验表明,该算法能最大化的保证融合后的图像信息,得到高清晰度的融合图像。     

具有运动补偿的多值量化块截断编码

报道了一种新的活动图象编码算法,称为具有运动补偿的多值量化块截断编码．模拟结果表明：这种新算法比现有的其它同类算法有更好的性能,压缩比为７５,信噪比为３５ｄＢ,在现有个人计算机上可以用软件实时实现．     

关联集合在协同过滤推荐算法中的应用研究

为了提高电子商务推荐系统的精度,提出了基于关联集合的协同过滤推荐算法,该算法通过频繁项集生成算法生成一系列频繁项集,然后通过合并处理过滤掉与用户关联很小的一些噪音项目,从而使协同过滤算法更加有效。该算法在推荐精度上比传统的方法优越。     

关联规则在电压暂降分析中的应用

基于实际电压暂降历史记录,利用传统关联规则算法Apriori算法思想作进一步改进,对电压暂降历史记录进行多维关联规则挖掘,探求符合真实规律的电压暂降强关联规则,并对得到的关联规则的价值进行分析.研究证明了关联规则在电压暂降研究分析领域有着良好的应用前景,为相关电力部门制定电压暂降预防或治理决策提供很多有重要价值的参考.     

Super twisting control algorithm for the attitude tracking of a four rotors UAV

This paper deals with the design and implementation of a nonlinear control algorithm for the attitude tracking of a four-rotor helicopter known as quadrotor. This algorithm is based on the second order sliding mode technique known as Super-Twisting Algorithm (STA) which is able to ensure robustness with respect to bounded external disturbances. In order to show the effectiveness of the proposed controller, experimental tests were carried out on a real quadrotor. The obtained results show the good performance of the proposed controller in terms of stabilization, tracking and robustness with respect to external disturbances.