Design of dispersive multilayer with particle swarm optimization method

<正>We present a new and efficient method for the design of dispersive multilayer by employing a particle swarm optimization(PSO) technique.Its mathematical background is given and an adaptive PSO is realized with computer code.Two practical designing tasks are solved with this method,and the obtained results are competitive compared with other published structures.The adaptive PSO method demonstrates its merits of fast convergence and powerful global search ability,and could be used as a valuable tool for the optical thin film design.     

一种改进的SUSAN角点提取方法

针对基本SUSAN算法存在漏检测、处理速度慢以及容易产生伪角点等问题,提出了一种改进的SUSAN角点提取算法。首先对图像的像素点按边缘点、内部点和背景点进行分类,在此基础上只对边缘点进行SUSAN算法处理,然后检查已经提取到的所有角点,剔除同一区域范围内的伪角点,从而实现对大部分角点的快速、准确提取。实验结果表明,该算法的运算速度比改进前提高约一倍,能够较准确地检测到目标角点。     

解非线性方程组的一类算法

§1.引言 求解线性方程组 a_i~Tx=b_i,i=1,2,…,n,(1.1)其中a_1,a_2,…,a_n线性无关. 设y~((1))为初值,U~((1))为任意非奇异n阶矩阵,我们用如下方法求解方程组(1.1). 先考虑前k-1个方程组成的亚定方程组 a_i~Tx=b_i,i=1,2,…,k-1.设{U~((k))}={a_1,a_2,…,a_(k-1)},这里{U~((k))}表示由U~((k))的列组成的子空间.显然,rank(U~((k)))=n-b+1.若y~((k))是相应的亚定方程的一个特解,则将其看作方程组     

基于Goose LDW-PSO的管壳式换热器优化设计

管壳式换热器在工业中的应用越来越广泛,对于设计者和使用者来说使其费用最小化是一个很重要的目标。本文以最小化管壳式换热器的总费用为优化目标,提出了运用基于雁群启示的惯性权重线性下降粒子群优化算法(Goose LDW-PSO)对其进行优化设计。为了验证这种方法的有效性,用Goose LDW-PSO对管壳式换热器进行了优化设计,并与原始设计结果进行了比较。比较结果表明,虽然管子数目增加,但是换热器的总费用比传统方法少了很多。     

A hybrid scheme for geoacoustic inversion

A hybrid inversion scheme of geoacoustic parameters, which combines dispersion characteristics of normal modes with transmission loss, has been proposed based on the facts that different parameters have different effects on sound field. First, considering the dispersion characteristics of normal modes were sensitive to the density and the sound speed of seabottom, and not sensitive to the seabottom attenuation coefficient, the group time delays of different modes and different frequencies were acquired through adaptive optimal kernel time-frequency representation, then the group time delays were taken as the cost function, and using a global optimal algorithm, the seabottom density and the profile of seabottom sound speed were deduced. Successively, the validity of inversion results was evaluated by the a posteriori probability. Last, the attenuation coefficient of sediment is inverted using the transmission loss data recorded from the ship radiation noise. The validity of the total inversion results has been evaluated by making use of the matched field processing source localization.     

Potential-Decomposition Strategy in Markov Chain Monte Carlo Sampling Algorithms

We introduce the potential-decomposition strategy （PDS）, which can be used in Markov chain Monte Carlo sampling algorithms. PDS can be designed to make particles move in a modified potential that favors diffusion in phase space, then, by rejecting some trial samples, the target distributions can be sampled in an unbiased manner. Furthermore, if the accepted trial samples are insumcient, they can be recycled as initial states to form more unbiased samples. This strategy can greatly improve efficiency when the original potential has multiple metastable states separated by large barriers. We apply PDS to the 2d Ising model and a double-well potential model with a large barrier, demonstrating in these two representative examples that convergence is accelerated by orders of magnitude.     

基于组合模拟波段的油菜菌核病早期诊断方法研究

应用组合模拟波段建立的线性和非线性判别模型实现了油菜菌核病的早期诊断。采集油菜健康叶片80个,菌核病染病叶片100个,采用预处理算法与连续投影算法(SPA)相结合提取组合模拟波段,分别建立偏最小二乘法(PLS)、多元线性回归(MLR)和最小二乘-支持向量机(LS-SVM)模型。通过比较,最优PLS判别的预处理分别为直接正交信号校正(DOSC)、De-trending和原始反射光谱(Raw),准确率分别为100%,95.7%和95.7%。应用组合模拟波段的最优线性模型为SPA-MLR(DOSC)和SPA-PLS(DOSC)模型,准确率均为100%,基于DOSC、De-trending和Raw组合模拟波段的SPA-LS-SVM模型的判别准确率均为100%。结果表明,基于组合模拟波段进行油菜菌核病早期诊断是可行的,为油菜菌核病的早期诊断及病害监测仪器的开发提供了方法和依据。     

基于脉冲耦合神经网络的拉曼光谱定性分析

通过对脉冲耦合神经网络(pulse coupled neural network,PCNN)和拉曼光谱定性分析的研究,提出了基于PCNN的拉曼光谱定性分析方法.首先,利用PCNN神经元的疲劳与不应期特性将拉曼光谱数据进行编码;然后,基于改进的Horspool算法将检测样品对应编码与基码数据库中的所有基码逐一匹配,并得到各对应的匹配相似度,进而判定样品类别.相关实验和数据分析证明了该文方法的准确性和有效性.同时,该文方法避免了目前基于谱模版定性分析方法中待测样品拉曼光谱特征谱峰难以确定以及匹配分析冗余度高等不足,且对存储空间的要求仅为后者的5.8%.     

基于暗像元的Hyperion高光谱影像大气校正

大气是影响遥感定量分析与应用的重要因素。该文利用暗像元大气校正算法,在IDL平台下,从Hyperion传感器的可见光-近红外波段逐通道提取大气光学厚度信息,并利用该数据实现对Hyperion数据大气校正的目的。研究结果表明,大气光学厚度随着通道中心波长的增加而减小,即与中心波长成负相关。光学厚度与中心波长的最佳经验模型为线性模型,模型的回归系数为0.912 3。通过分析校正前后的水体光谱曲线可知,大气的衰减作用使得卫星遥感信号不能正确表现自然水体的表观光学特性和内在光学特性,且对水体样本层次变化不敏感。在蓝绿波段,大气对光谱数据的污染最为严重,该波段的光谱特征与自然水体的理论光学特性完全相背离。由大气光学厚度光谱特性和自然水体光学特性可知,经过"暗像元"算法校正过的影像数据的质量得到显著改善。在缺少同步大气垂直剖面参数的情况下,暗像元算法将是Hyperion数据一种行之有效的大气效应消除方法。     

基于单通道算法的HJ-1B与Landsat 5 TM地表温度反演一致性研究

针对传感器参数与Landsat 5 TM较为相近的环境减灾卫星HJ-1B的热红外数据是否能达到与TM6反演地表温度同样的效果的问题,作者获取了2009年4月15日覆盖北京地区相同范围的HJ-1B影像和Landsat 5 TM影像,采用Ji m啨nez-Mu oz和Sobrino的普适性单通道算法,通过遥感数据获取反演参数,对研究区的地表温度进行反演,并对两类数据反演结果的一致性进行了分析和评价。通过对反演结果的统计分析和分级填图表明,基于普适性单通道算法的HJ-1B与TM的热红外波段反演的地表温度在数值上和空间分布趋势上一致性较高。因此,具有较高时间分辨率和较大幅宽等优势的HJ-1B IRS数据在地表温度反演方面具有更大的潜力和应用范围。