基于FFT的傅里叶光谱Matlab仿真分析

采用迈克尔逊干涉装置测定了钠光灯和汞灯的干涉图,利用傅里叶光谱中存在的干涉图和光谱图的变换关系,通过快速傅里叶变换（FFT）的方法分析了钠光灯和汞灯的辐射光谱.Matlab仿真分析结果表明,采用傅里叶变换光谱可以清晰地展现辐射源的辐射光谱.     

变系数非线性Schrdinger方程的辛Runge-Kutta谱方法

用辛Runge-Kutta谱方法研究变系数非线性Schr(o)dinger方程.我们在空间方向用快速Fourier变换方法来离散二阶导数项,在时间方向用2级4阶隐式辛Runge-Kutta方法来离散一阶导数项,给出了变系数的非线性Schr(o)dinger方程的数值解法.数值结果显示该算法行之有效,它可以保持系统模方守恒和能量守恒的性质.     

求Hankel矩阵的逆矩阵的快速算法

利用Hankel矩阵的位移性质,得到了矩阵为Hankel矩阵的充要条件.从该充要条件出发,得到了求Hankel矩阵之逆矩阵的快速算法,计算复杂度为O(n2),而一般n阶矩阵求逆的复杂度为O(n3).     

定点FFT在TS201上的高效实现

针对美国模拟器件公司(ADI)推出的ADSP-TS201内部的DRAM存储器不适合标准结构快速傅里叶变换(FFT)对随机读写存储器要求的问题,采用SingLeton结构FFT,并给出了采用该结构FFT的程序流程,选择TS201内部适合定点FFT实现的汇编指令,通过合理安排指令并行和软件流水,在TS201上对定点FFT进行了高效实现.实例验证结果表明,完成32 K点FFT只需要0.46 ms,可用于GPS系统P码直捕的快速实现.     

Crust-mantle coupling in North China: Preliminary analysis from seismic anisotropy

Data from the CASN (Capital Area Seismograph Network), NSNC (National Seismograph Network of China), and IRIS (Incor-porated Research Institutions for Seismology) are compared with data from a temporary North China Seismic Array to obtain the background orientation of the horizontal crustal principal compressive stress at NE 95.1°±15.4° in North China. Data are corrected for disturbances of faults and irregular tectonics, and are used to constrain the fast SKS polarization at NE 110.2°±15.8° in North China. Individual station analyses suggests that there is consistently more than 10° difference between the polarizations of fast shear-wave in the crust and those of fast SKS phases. Azimuthally anisotropic phase velocities of Rayleigh waves at different periods also indicate an orientation change for fast velocity with depth. It suggests the crust-mantle coupling in North China follows neither the simple decoupling model nor the strong coupling model. Instead, it is possibly some inhomogeneous combination of two models or some gradual-change model of physical characteristics. This study shows that anisotropy in the crust and mantle could be multiply characterized more correctly and crust-mantle coupling could be analyzed further, if increasing near-field shear-wave splitting data that indicate crustal anisotropy, combined with the azimuthal anisotropy of Rayleigh waves, besides the result of SKS splitting travelling through lithosphere and surface GPS measurements.     

电特大目标散射的多层快速多极子高性能计算

针对电特大目标散射的并行多层快速多极子计算中出现的构造几何信息树所需资源过多、保存远场模式所需内存过大及计算雷达散射截面时间长等问题,根据主流并行计算机架构以及电特大目标的特点,提出了解决方案,实现了电特大目标散射的高效精确计算。通过对未知数超过5亿、电尺寸达到几千个波长的电特大目标的数值实验,表明本文方案的精确性和高效性。     

基于FFT的大型平面阵列方向图的综合方法

针对大型平面二维阵列,提出了一种快速的综合方法。首先根据单元激励初值,应用二维离散傅里叶逆变换(invert fast Fourier transform, IFFT)得出阵列方向图,然后与期望方向图比较,得出新的方向图,再应用二维快速傅里叶变换(fast Fourier transform, FFT)反算出新的单元激励。如此反复,直到方向图满足设计要求。该算法直接对大型平面二维阵列进行优化而不是针对一维线阵或小型阵列,而且天线单元数大于5 000。最后两个6 400（80×80）单元阵列的仿真结果表明该方法实用、高效。     

预条件CMRH方法加速求解半空间三维电磁散射问题

为了高效求解半空间三维电磁散射问题中离散电场积分方程产生的大型对称稠密复线性矩阵,将半空间多层快速多极子方法与CMRH方法相结合,其中多层快速多极子方法用于加速CMRH方法中的矩阵矢量乘运算.为了验证文中方法的有效性,分别计算了位于有耗半空间的圆柱体、长方体以及某导弹模型的散射特性. 结果表明,所提出的方法不仅可以滤除高频误差,平滑低频误差,而且能使求解半空间离散电场积分方程的迭代次数和计算时间比现在广泛使用的广义最小余量法显著减少. 同时,CMRH方法与稀疏近似逆预条件、对称超松弛预条件结合可进一步提高求解效率.     

Compressed sensing based channel estimation for fast fading OFDM systems

A compressed sensing (CS) based channel estimation algorithm is proposed by using the delay-Doppler sparsity of the fast fading channel. A compressive basis expansion channel model with sparsity in both time and frequency domains is given. The pilots in accordance with a novel random pilot matrix in both time and frequency domains are sent to measure the delay-Doppler sparsity channel. The relatively nonzero channel coefficients are tracked by random pilots at a sampling rate significantly below the Nyquist rate. The sparsity channels are estimated from a very limited number of channel measurements by the basis pursuit algorithm. The proposed algorithm can effectively improve the channel estimation performance when the number of pilot symbols is reduced with improvement of throughput efficiency.     

门式启闭机快速设计平台的研究与开发

分析了门式启闭机结构组成及设计过程中存在的问题,并基于CATIA软件和ANSYS软件的门机快速设计平台的研究与开发,重点介绍了该平台的结构、模块和主要界面的设计,通过实例演示结果,总结本平台的特点和实际应用价值。