随机并行梯度下降算法用于光纤激光相干合成的理论与实验研究

介绍了随机并行梯度下降(SPGD)算法用于相干合成的基本理论,利用数值模拟的方法对实际相干合成实验中涉及到的算法评价函数、扰动电压分布等参数进行优化选取,确定了实验中应选择的最佳评价函数、扰动电压分布和扰动方式.利用数字信号处理器(DSP)执行SPGD算法,实时控制各路光束的相位,实现了三路瓦量级保偏光纤放大器输出光束的相干合成.实验结果表明,SPGD算法能够有效控制各路光纤激光的相位,系统闭环将合成光束目标圆孔内的能量提高了2.62倍,合成效率达到了理想情形的87%,远场光斑对比度为85%.     

从一维光晶格中释放的任意子噪声关联函数研究

首先求解具有delta函数型相互作用的任意子气体的含时薛定谔方程,给出了其多体波函数的解析解,并在此基础上详细分析了无相互作用情形和有相互作用情形下任意子噪声关联函数的特性.对于有相互作用的任意子气体,其噪声关联呈现出与无相互作用情形下不同的特性:散射相位具有一定的空间分布,一系列线性而不是尖峰出现在噪声关联函数中;线性的宽度、取向以及位置与任意子的统计参数和粒子间相互作用强度的关系都非常密切.特别地,在TG极限下,也就是相互作用趋于无限大的情形下,粒子间散射相位变为,任意子的噪声关联函数图样与无相互作用情形下的图样完全相反.     

基于函数映射的快速傅里叶变换算法

给出了一种新的快速傅里叶变换算法.算法利用了傅里叶变换因子C_N^kn、S_N^kn的对称特性,将函数序列x(n)个数压缩至四分之一.对其压缩后的函数序列,按其相邻函数值之差映射为函数p(n),同时对傅里叶变换因子C_N^kn、S_N^kn按累进求和映射为A_N^kn、B_N^kn.不同于FFT算法要求N为2的整数次幂,该算法中N可为任何偶数.对诸如方波、三角波、锯齿波及可分解为阶梯波的光学图象、特别是二值光学图象,能极大地减少计算量,某些情形低于FFT算法的计算量.     

基于相位掩模的粒子三维定位

快速、精确地对粒子进行三维定位在生命科学、材料科学、工业检测等领域具有重要的应用价值。传统的粒子定位方法由于运算量繁重，难以满足快速、精确的需求。文章提出了一种新的基于相位掩模的粒子三维定位方法。采用Fienup优化算法设计位于4f系统频谱面上的相位掩膜，针对不同深度的点光源获得一系列点扩散函数；结合粒子位置和所成图像进行神经网络训练，可在8μm轴向范围内经单次测量实现目标粒子在三维空间中的高精度定位。两组模拟设计的数值结果表明所提方法能够快速高效地完成稀疏粒子的三维定位，在细胞粒子成像定位等方面具有重要的应用价值。     

虚阶Bessel函数的计算

给出了计算虚阶Bessel函数及其导数的完整算法。数值结果表明,计算精度可达10位以上有效数字。此外,所给出的逆推法可推广到复阶数的情形。     

基于改进粒子群优化算法的混沌系统参数估计方法

估计混沌系统的未知参数是混沌控制与同步中必须解决的关键问题.利用群集智能的新进展粒子群优化算法(PSO)的全局搜索能力，从初始粒子群的产生、目标函数的处理的角度改进PSO，将改进的PSO引入混沌系统参数估计和在线估计.仿真试验表明，改进算法具有良好的适应性、较高的收敛可靠性及精度，对信号叠加噪声的情形也具有较高的鲁棒性，是混沌系统参数估计的一种成功算法. 关键词： 混沌系统 参数估计 在线估计 粒子群优化算法     

基于鲁棒损失函数的标签有噪信号调制方式识别

针对现实信号调制方式标注易发生错误, 即训练数据集中信号调制方式标签存在噪声情形, 我们选取l₁模损失函数及其推广形式作为对标签噪声具有鲁棒性的损失函数, 结合深度卷积神经网络优良的自动特征提取能力, 提出一种针对信号调制方式存在误判噪声的深度学习算法。该算法在训练数据集合标签噪声率达50%情形下, 对信号调制方式的识别准确率依然保持较高水平。相反, 对于采用通常的交叉熵作为损失函数的深度卷积神经网络, 其已无法对信号调制方式进行分类识别。在公开的数据集上的数值实验表明, 所提算法对于标签有噪信号调制方式识别具有较强的鲁棒性。     

MATLAB在量子力学学习中的应用

指出了《工科量子力学学习中的常用数学工具》一文中的一些差错,列出了正确的公式.量子力学的公式比较多,解决计算问题的最佳工具应该是MATLAB.用MATLAB说明了极限的算法,积分的算法,常微分方程的解法,狄拉克函数的表示和算法,伽玛函数和贝塔函数的用法,特殊函数的算法.以一维线性谐振子为例,说明了MATLAB在量子力学中的应用.MATLAB还能计算氢原子中电子出现的概率密度,并用图形表现出来.     

基于电磁超材料的两种等效参数提取算法的比较分析

基于传统反演算法和Kramers-Kronig关系改进算法, 分别提取弱耦合和强耦合超材料渔网结构模型的等效参数, 并对两种算法的有效性及普适性进行了探讨.理论分析及计算结果表明, 传统的反演算法可以准确地反演弱、强耦合情形下电磁超材料结构的等效参数, 但计算复杂度较高;而基于Kramers-Kronig关系的改进算法巧妙地降低了计算的复杂度, 能简单准确地提取弱耦合情形下电磁超材料结构的等效参数, 但对于强耦合情形则不适用, 原因在于强耦合情形破坏了Kramers-Kronig关系的解析且连续性要求. 研究结果拓展了等效媒质理论并可为新的电磁超材料的设计提供理论参考. 关键词： 超材料 反演算法 Kramers-Kronig关系 等效参数     

从一维光晶格中释放的任意子噪声关联函数研究

首先求解具有delta函数型相互作用的任意子气体的含时薛定谔方程,给出了其多体波函数的解析解,并在此基础上详细分析了无相互作用情形和有相互作用情形下任意子噪声关联函数的特性。对于有相互作用的任意子气体,其噪声关联呈现出与无相互作用情形下不同的特性：散射相位具有一定的空间分布,一系列线性而不是尖峰出现在噪声关联函数中;线性的宽度、取向以及位置与任意子的统计参数和粒子间相互作用强度的关系都非常密切。特别地,在TG极限下,也就是相互作用趋于无限大的情形下,任意子的噪声关联函数图样与无相互作用情形下的图样完全相反。     

Noise-insensitive iterative method for interferogram processing

We have developed and numerically evaluated an iterative algorithm for interferogram processing, which includes the Fourier-transform method, the Gerchberg-Papoulis algorithm and Wiener's filter-based regularization used in combination. Using a signal-to-noise ratio of not less than 1, it has been possible to reconstruct the phase of an object field with an accuracy better than 5%.     

Optimal nonmonotonic convergence of the iterative Fourier-transform algorithm

The increase of the monotonic convergence rate is an important issue for iterative Fourier-transform algorithms. However, the steepest monotonic convergence of the iterative Fourier-transform algorithm does not always promise an optimal solution in the design of a diffractive optical element. The optimal nonmonotonic convergence of the iterative Fourier-transform algorithm is investigated by employing a microgenetic algorithm. The proposed hybrid scheme of the iterative Fourier-transform algorithm and the microgenetic algorithm show nonmonotonic convergence, and this results in a superior design.     

非相干照明条件下的ptychographic iterative engine成像技术

在传统多波长相干衍射成像理论的基础上提出适用于 X-射线和电子束等非相干光源照明成像的改进多波长ptychographic iterative engine 方法, 同时将小孔形状和照明光谱信息用于叠代计算, 可以在非相干照明条件下精确重建出物体的强度透射像和相位透射像, 并对光源带宽对重建精度的影响进行了分析, 对于解决如何在非相干照明条件下对大尺寸物体进行精确相位成像的问题具有较好的科研和实用价值.     

Phase quantization of a grating without altering the diffraction pattern

Quantization of the phase-delay profile of a diffractive optical element often leads to unwanted deviations of considerable extent in the diffraction pattern. A method for avoiding this flaw for periodic phase gratings is described. The idea is to forgo strict periodicity and use the new degrees of freedom thus obtained to compensate for quantization-related deviations. The method is demonstrated for Fourier-array illuminator gratings designed with an iterative Fourier-transform algorithm.     

A coarse-to-fine kernel matching approach for mean-shift based visual tracking

Mean shift is an efficient pattern match algorithm. It is widely used in visual tracking fields since it need not perform whole search in the image space. It employs gradient optimization method to reduce the time of feature matching and realize rapid object localization, and uses Bhattacharyya coefficient as the similarity measure between object template and candidate template. This thesis presents a mean shift algorithm based on coarse-to-fine search for the best kernel matching. This paper researches for object tracking with large motion area based on mean shift. To realize efficient tracking of such an object, we present a kernel matching method from coarseness to fine. If the motion areas of the object between two frames are very large and they are not overlapped in image space, then the traditional mean shift method can only obtain local optimal value by iterative computing in the old object window area, so the real tracking position cannot be obtained and the object tracking will be disabled. Our proposed algorithm can efficiently use a similarity measure function to realize the rough location of motion object, then use mean shift method to obtain the accurate local optimal value by iterative computing, which successfully realizes object tracking with large motion. Experimental results show its good performance in accuracy and speed when compared with background-weighted histogram algorithm in the literature.     

Method for designing arbitrary two-dimensional continuous phase elements

We propose a method for designing arbitrary two-dimensional continuous phase elements. The phase anomalies that are due to amplitude zeros that occur in conventional design methods can be avoided completely with this method. Therefore the method is also useful for designing holographic elements that are free from amplitude zeros. The method is based on an iterative Fourier-transform algorithm. In the iteration process the method operates on the unwrapped phase. Consequently, a subsequent continuation step is not needed.     

Algorithm for reconstruction of digital holograms with adjustable magnification

A new algorithm that allows for reconstruction of digital holograms with adjustable magnification is proposed. The algorithm involves two reconstruction steps implemented by a conventional single Fourier-transform algorithm. The advantages of the algorithm lie in its adaptability to various object sizes and recording distances as well as in its capability to maintain the pitch of a reconstructed image, independent of the reconstruction distance and wavelength for objects larger than a CCD. The feasibility of the algorithm is demonstrated by experiments. The algorithm is especially useful for reconstructing color holograms and for metrological applications.     

A circle similarity algorithm for an automatic circular decomposition of blood cell images

This paper presents an iterative algorithm for circular decomposition which investigates the separation of overlapped circular particles of a binary image, in order to locate their center coordinates and to estimate their radii. Since this algorithm is based on the measure of a circle similarity of an object in an image to execute a search for concavities, object segmentation and circle recognition, its implementation is simpler than the algorithm based on polygonal approximation. In this work we compare the accuracy and robustness of the proposed circle similarity algorithm with a polygonal approximation based algorithm using synthetic images and real blood cell images. Both the algorithms are able to decompose connected blood cells. However, the input parameters of the polygonal approximation method shows high sensitivity to the shape or agglomeration of an object, while the proposed algorithm demonstrates more stable performance.     

基于预滤波迭代梯度法的运动估计

提出一种对小平移和大平移图像序列进行运动估计的新算法 预滤波迭代梯度法,预滤波迭代梯度法就是先对图像进行低通滤波,然后用迭代梯度法进行运动估计。结果表明,该方法比梯度法、预滤波梯度法和迭代梯度法具有更高的估计精度,而且可以很好地抑制噪声的影响。     

Three-dimensional electromagnetic nonlinear inversion in layered media by a hybrid diagonal tensor approximation: Stabilized biconjugate gradient fast Fourier transform method

This paper presents an efficient three-dimensional nonlinear electromagnetic inversion method in a multilayered medium for radar applications where the object size is comparable to the wavelength. In the first step of this two-step inversion algorithm, the diagonal tensor approximation is used in the Born iterative method. The solution of this approximate inversion is used as an initial guess for the second step in which further inversion is carried out using a distorted Born iterative method. Since the aim of the second step is to improve the accuracy of the inversion, a full-wave solver, the stabilized biconjugate-gradient fast Fourier transform algorithm, is used for forward modelling. The conjugate-gradient method is applied at each inversion iteration to minimize the functional cost. The usage of an iterative solver based on the FFT algorithm and the developed recursive matrix method combined with an interpolation technique to evaluate the layered medium Green's functions rapidly, makes this method highly efficient. An inversion problem with 32 768 complex unknowns can be solved with 1% relative error by using a simple personal computer. Several numerical experiments for arbitrarily located source and receiver arrays are presented to show the high efficiency and accuracy of the proposed method.