区间正交小波变换域FLP算法及其在捷联寻北中的应用

针对机抖激光陀螺角随机游走和发动机干扰等影响静态捷联寻北精度的问题,提出了一种新的基于区间正交小波变换的前向线性预测算法。该算法利用前向线性预测技术以及区间正交小波变换抑制边界效应的能力,有效地减小了角随机游走和发动机干扰。车载实验证明该算法的有效性。     

采用局域像素匹配的随机抽样一致改进算法

为提高图像拼接的配准精度和稳健性,提出基于局域像素匹配的随机抽样一致改进算法.在完成尺度不变特征变换算子或其他算子图像特征提取、特征匹配之后,利用独立于特征匹配点的局域像素,通过参考图像局域像素与映射的待拼接图像局域像素匹配,优选4对最佳特征匹配点,确定最佳单应矩阵.实验结果表明:与随机抽样一致经典算法相比,该方法未明...     

激光陀螺数字抖动控制方法与特性

针对传统的模拟抖动控制系统体积大、灵活性差的缺点,设计了一种基于单片机的新的激光陀螺数字抖动控制方法,建立了陀螺抖动的数学模型,比较研究了传统的模拟正弦波驱动和新的数字方波驱动的抖动特性,指出了后者不同于前者的抖幅变化律及非线性的随机噪声注入方式。仿真和实验证明,该方法能很好满足激光陀螺抖动控制要求,保证陀螺性能。     

有限马氏链最优停止的线性规划解

离散时间的有限状态马尔可夫链最优停止的值函数存在的一个充分条件是所对应的线性规划有解,且其最优解等于值函数,本文证明这个条件还是必要的。     

随机频率步进雷达成像分析

随机频率步进信号兼具步进频率雷达和宽带噪声雷达的特点,不仅可以降低系统瞬时带宽和数据采样率,还具有优良的低截获概率(LPI)、电磁兼容性(EMC)和抗射频干扰(ARFI)特性.分析了随机频率步进信号的相关输出及模糊函数的统计特性,如一阶矩、二阶矩和方差等,并与均匀频率步进信号做了抗干扰性能的比较.提出并分析了相关输出结...     

考虑多轴应力与共振影响的随机振动疲劳寿命预测

目前工程上计算结构随机疲劳寿命时,仍经常采用基于单轴拉-压疲劳寿命(Stress-Number of cycles,S-N)曲线的应力寿命方法.虽然使用简单方便,但这种方法不仅忽视了单轴S-N曲线且不能准确反映结构在多轴应力状态下的疲劳,还忽略了随机振动中共振对结构疲劳寿命的影响,因此该方法在预测结构在随机振动下的疲劳...     

挠性航天器变幅值输入成形姿态机动策略

针对变参数挠性航天器的姿态机动问题,在变幅值零振动成形器的基础上,提出了鲁棒性较强的变幅值零振动和零微分成形器设计方法,设计了鲁棒姿态机动策略.该机动策略的控制目标是,将航天器机动到期望状态的同时,消除挠性结构的残余振动.以含转动挠性太阳翼的航天器进行三轴姿态机动为例,进行数值仿真.仿真结果表明,该机动策略对挠性结构频...     

考虑黏弹性材料随机性的被动约束层阻尼梁动力学分析

采用传递函数方法研究了阻尼层黏弹性材料随机性对被动约束层阻尼(PCLD)梁动力学特性的影响。由Hamilton原理建立了PCLD梁六阶运动微分方程,通过引入状态向量,建立了系统的状态空间方程,利用传递函数方法得到了梁的固有频率和损耗因子。以黏弹性材料分数导数模型中的参数作为基本的随机变量,并假设其服从正态分布,使用Monte Carlo直接抽样法考察了材料模型参数的随机性对结构固有频率和模态损耗因子的影响。计算结果表明黏弹性材料参数的随机性对梁动力学特性的变异系数影响较大,模态损耗因子的变异系数最大值是材料参数变异系数的4.5倍。     

Adaptive random search for continuous simulation optimization

We present, analyze, and compare three random search methods for solving stochastic optimization problems with uncountable feasible regions. Our adaptive search with resampling (ASR) approach is a framework for designing provably convergent algorithms that are adaptive and may consequently involve local search. The deterministic and stochastic shrinking ball (DSB and SSB) approaches are also convergent, but they are based on pure random search with the only difference being the estimator of the optimal solution [the DSB method was originally proposed and analyzed by Baumert and Smith]. The three methods use different techniques to reduce the effects of noise in the estimated objective function values. Our ASR method achieves this goal through resampling of already sampled points, whereas the DSB and SSB approaches address it by averaging observations in balls that shrink with time. We present conditions under which the three methods are convergent, both in probability and almost surely, and provide a limited computational study aimed at comparing the methods. Although further investigation is needed, our numerical results suggest that the ASR approach is promising, especially for difficult problems where the probability of identifying good solutions using pure random search is small. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

Averaging frameworks for simulation optimization with applications to simulated annealing

We present two frameworks for designing random search methods for discrete simulation optimization. One of our frameworks is very broad (in that it includes many random search methods), whereas the other one considers a special class of random search methods called point‐based methods, that move iteratively between points within the feasible region. Our frameworks involve averaging, in that all decisions that require estimates of the objective function values at various feasible solutions are based on the averages of all observations collected at these solutions so far. Also, the methods are adaptive in that they can use information gathered in previous iterations to decide how simulation effort is expended in the current iteration. We show that the methods within our frameworks are almost surely globally convergent under mild conditions. Thus, the generality of our frameworks and associated convergence guarantees makes the frameworks useful to algorithm developers wishing to design efficient and rigorous procedures for simulation optimization. We also present two variants of the simulated annealing (SA) algorithm and provide their convergence analysis as example application of our point‐based framework. Finally, we provide numerical results that demonstrate the empirical effectiveness of averaging and adaptivity in the context of SA. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012