基于无衍射光的表面粗糙度三角测量及其灰色评定方法

 激光三角法是表面形貌非接触测量中的一种常用方法,在几何测量领域应用广泛。传统的激光三角法采用高斯光束作为指示光源,在机械扫描机构的配合下,通过对被测表面逐点扫描完成表面形貌的测量。采用新型的无衍射光替代传统激光光源,解决了普通高斯光束存在的“焦深”问题,简化了机械结构。并采用基于灰色系统理论的灰色滤波进行表面形貌的分离与评定,克服了原有方法对测量数据样本量和统计特性的依赖,并通过实验表明该系统能够准确地完成表面形貌的三维测量,所提出的灰色评定方法能够比较有效地进行表面形貌的分离与评定。     

多模跟踪技术在轮式侦察车图像处理器的应用

为解决目标旋转形变、遮挡、光照变化等目标跟踪的难题,对粒子滤波和尺度不变特征变换（SIFT）算法进行了改进,结合两种算法提出了决策主导模式的多模跟踪技术。该技术采用粒子滤波预测目标位置进行粗定位,SIFT特征匹配进行精定位的方法,在解决上述难题上有很好的鲁棒性。将该技术应用于轮式侦察车图像处理器,并进行了各种实验验证,结果证明了提出算法的有效性。     

北半球环流系统季节内及年际以上振荡信号的信息传输

利用NCEP/NCAR月平均高度场再分析资料,分别提取季节内和年际以上振荡的基本特征和形式,运用信息传输理论分析这两种振荡信号的信息在低纬度与中高纬度间的传输.发现季节内振荡信号信息损失率较年际以上的偏大,且在特定地区这两种振荡信号的信息具有反向传输的特征;空间传输的水平分布上,两种振荡信号均表现为纬向上低纬度信息损失率大且海陆分布差异显著;空间传输的垂直分布上,年际以上振荡信号的低纬度高空信息损失率较大,中高纬度从对流层至平流层底信息损失率都较小,而季节内振荡信号则是低空信息损失率大,高空信息损失率小. 关键词： 滤波 高度场 信息损失率     

磁过滤器电流对非晶碳薄膜摩擦学特性影响的研究

研究了过滤阴极真空电弧技术中,不同的磁过滤器电流下(5—13 A),制备的四面体非晶碳(ta-C)薄膜对摩擦学特性的影响.通过对薄膜厚度,薄膜结构以及薄膜表面粗糙度随磁过滤电流的变化结果进行了测试,结果表明,随着磁过滤器电流的增大,薄膜的sp³键含量逐渐减少,表面粗糙度从0.13增大到0.38.磁过滤器电流在5 A时,薄膜的摩擦系数最小约为0.08,当电流增大到7 A时,摩擦系数显著增大,磁过滤器电流从7 A增大到13 A时,薄膜的摩擦系数再次减小约为0.1. 关键词： 四面体非晶碳 过滤阴极真空电弧 磁过滤器电流 摩擦系数     

扩展卡尔曼滤波和不敏卡尔曼滤波在实时雷达回波反演大气波导中的应用

为了改善雷达回波反演大气波导(RFC)方面存在的单时次、单方位角反演的问题,提出利用扩展卡尔曼滤波和不敏卡尔曼滤波的反演算法对大气波导结构的多方位角实时跟踪反演. 在卡尔曼滤波方法中分别给出大气波导结构的参数化方程、观测方程、滤波算法的状态转移方程,最后导出滤波反演算法的迭代求解流程. 在大气波导结构不随时间变化和随时间变化的两种条件下,对扩展卡尔曼滤波和不敏卡尔曼滤波算法进行数值实验. 实验结果表明,不敏卡尔曼滤波更适用于RFC这高度非线性反演问题,它可能今后为大气波导结构多方位角实时跟踪反演的业务化运行提供理论基础与技术保证. 关键词： 大气波导 雷达回波 扩展卡尔曼滤波 不敏卡尔曼滤波     

On the fractional-order extended Kalman filter and its application to chaotic cryptography in noisy environment

In this paper via a novel method of discretized continuous-time Kalman filter, the problem of synchronization and cryptography in fractional-order systems has been investigated in presence of noisy environment for process and output signals. The fractional-order Kalman filter equation, applicable for linear systems, and its extension called the extended Kalman filter, which can be used for nonlinear systems, are derived. The result is utilized for chaos synchronization with the aim of cryptography while the transmitter system is fractional-order, and both the transmitter and transmission channel are noisy. The fractional-order stochastic chaotic Chen system is then presented to apply the proposed method for chaotic signal cryptography. The results show the effectiveness of the proposed method.     

Sequential smoothing for turning point detection with application to financial decisions

A fundamental problem in financial trading is the correct and timely identification of turning points in stock value series. This detection enables to perform profitable investment decisions, such as buying‐at‐low and selling‐at‐high. This paper evaluates the ability of sequential smoothing methods to detect turning points in financial time series. The novel idea is to select smoothing and alarm coefficients on the gain performance of the trading strategy. Application to real data shows that recursive smoothers outperform two‐sided filters at the out‐of‐sample level. Copyright © 2012 John Wiley & Sons, Ltd.     

AN ADAPTIVE OPTIMAL KALMAN FILTER FOR STOCHASTIC VIBRATION CONTROL SYSTEM WITH UNKNOWN NOISE VARIANCES

In this paper, an optimal criterion is presented for adaptive Kalman filter in a control system with unknown variances of stochastic vibration by constructing a function of noise variances and minimizing the function. We solve the model and measure variances by using DFP optimal method to guarantee the results of Kalman filter to be optimized. Finally, the control of vibration can be implemented by LQG method.     

Entropy in Subordination and Filtering

We propose a stochastic model of transmitting random information at random time. In this model, the signal is observed as a random sampling according to an increasing stable stochastic process. Thus we are given a subordinate stochastic process which is a typical irreversible process. As the characteristic of this phenomea we observe the loss of entropy.