模糊处理变结构神经网络日负荷预测方法研究

对于受不确定因素影响的日电力负荷,首次提出了基于模糊分类规则的变结构神经网络负荷预测模型,考虑从两方面改进预测精度,一个方面是通过模糊分类规则,使过去的负荷数据分为不同气候特征,选用同类特征数据进行预测,另一方面是通过神经网络变结构优化,确定最优网络和最优拟合逼近,从而得到最优的预测结果,这种新方法同时考虑了天气因素的影响和神经网络的最优确定,因此,较大提高了日负荷预测的精度。     

《测量不确定度表示指南ISO1993（E）》的问题简析

简要介绍了《测量不确定度表示指南ISO1993（E）》的一系列缺陷与执行中的困难。     

高精度近场动力学方法:一维键型研究

近些年发展起来的近场动力学方法对于模拟复杂的断裂破坏问题具有显著优势.然而,计算精度不高一直是影响该方法进一步发展的瓶颈问题之一.区域积分不精确和键缺失导致的边界效应是降低该方法计算精度的两个主要原因.针对一维键型近场动力学模型,本文通过修正微模量提高区域积分的精度,通过理性构建固定边界和力边界虚拟键改善边界效应,建立了高精度近场动力学方法.数值结果表明,与经典的近场动力学方法相比,本文方法显著提高了计算精度,准静态常应变问题甚至能够达到机器精度.     

Minimizing convex quadratics with variable precision conjugate gradients

We investigate the method of conjugate gradients, exploiting inaccurate matrix‐vector products, for the solution of convex quadratic optimization problems. Theoretical performance bounds are derived, and the necessary quantities occurring in the theoretical bounds estimated, leading to a practical algorithm. Numerical experiments suggest that this approach has significant potential, including in the steadily more important context of multiprecision computations.     

基于Beta函数及其偏导数的广义积分的高精度快速计算

考虑Beta函数偏导数的计算以及与此相关的广义积分的高精度快速计算问题.首先将Beta函数B(x,y)的定义扩展到整个复平面上,并建立了在整个复平面上Beta函数B(x,y)的偏导数的递推公式.对许多广义积分我们给出Beta函数偏导数的表示形式,因而利用Beta函数的偏导数计算这些广义积分.数值计算表明,算法无论从计算精度还是计算速度,远好于数值积分.另外,得到了B_(p,q)(x,y)存在闭形式的条件,并给出一些广义积分的闭形式.     

基于精度的属性约简新方法

自Pawlak提出粗糙集概念以来,人们就一直对粗糙集的近似精度很感兴趣,出现了不少有关近似精度的文献.在粗糙集理论中,精度是量化由粗糙集边界引起的不精确性的一种重要数字特征.在分析传统精度和基于等价关系图的过剩熵的近似精度的基础上,提出了一种新的精度定义.比较发现,新定义的精度更具有合理性.同时把这个新定义的精度运用到了属性约简上,通过实例比较发现,本文提出的属性约简更具有可行性.     

Efficient and stable perfectly matched layer for CEM

An efficient unsplit perfectly matched layer for numerical simulation of electromagnetic waves in unbounded domains is derived via a complex change of variables. In order to surround a Cartesian grid with the PML, the time-dependent PML requires only one (scalar) auxiliary variable in two space dimensions and six (scalar) auxiliary variables in three space dimensions. It is therefore cheap and straightforward to implement. We use Fourier and energy methods to prove the stability of the PML. We extend the stability result to a semi-discrete PML approximated by central finite differences of arbitrary order of accuracy and to a fully discrete problem for the ‘Leap-Frog’ schemes. This makes precise the usefulness of the derived PML model for longtime simulations. Numerical experiments are presented, illustrating the accuracy and stability of the PML.     

大气湍流对天文望远镜光电导行精度的影响

讨论了由大气湍流造成的望远镜导行误差,这一误差将给望远镜光电导行的精度带来较大影响。其中使用单点源目标的导行精度受限于大气相干长度和大气相干时间,而多点源目标及面源的导行精度还与湍流随高度的变化有关。通过分析和仿真(数值模拟)结果表明,现代天文观测必须考虑大气湍流对光电导行精度的影响。通过延长曝光时间可以有效降低湍流大气的影响,同时也降低了光电导行的反馈控制频率。当导行信标为多星或面源则可在一定程度上降低高层大气湍流带来的光电导行误差,从而可以适度减少光电导行曝光时间,提高其反馈控制频率。     

一种基于图像融合和卷积神经网络的相位恢复方法

相位恢复法利用光波传输中某一(或某些)截面上的光强分布来传感系统波前,其结构简单,不易受震动及环境干扰,被广泛应用于光学遥感和像差检测等领域.传统相位恢复法采用迭代计算,很难满足实时性要求,且在一定程度上依赖于迭代转换或迭代优化初值.为克服上述问题,本文提出了一种基于卷积神经网络的相位恢复方法,该方法采用基于小波变换的图像融合技术对焦面和离焦面图像进行融合处理,可在不损失图像信息的同时简化卷积神经网络的输入.网络模型训练完成后可依据输入的融合图像直接输出表征波前相位的4-9阶Zernike系数,且波前传感精度均方根(root-mean-square,RMS)可达0.015λ,λ=632.8 nm.研究了噪声、离焦量误差和图像采样分辨率等因素对波前传感精度的影响,验证了该方法对噪声具有一定鲁棒性,相对离焦量误差在7.5%内时,波前传感精度RMS仍可达0.05λ,且随着图像采样分辨率的提升,波前传感精度有所改善,但训练时间成本随之增加.此外,分析了实际应用中,当系统像差阶数与网络训练阶数略有差异时,本方法所能实现的传感精度,并给出了解决方案.     

Fast Face-Recognition Optical Parallel Correlator Using High Accuracy Correlation Filter

We designed and fabricated a fully automatic fast face recognition optical parallel correlator [E. Watanabe and K. Kodate: Appl. Opt. 44 (2005) 5666] based on the VanderLugt principle. The implementation of an as-yet unattained ultra high-speed system was aided by reconfiguring the system to make it suitable for easier parallel processing, as well as by composing a higher accuracy correlation filter and high-speed ferroelectric liquid crystal-spatial light modulator (FLC-SLM). In running trial experiments using this system (dubbed FARCO), we succeeded in acquiring remarkably low error rates of 1.3% for false match rate (FMR) and 2.6% for false non-match rate (FNMR). Given the results of our experiments, the aim of this paper is to examine methods of designing correlation filters and arranging database image arrays for even faster parallel correlation, underlining the issues of calculation technique, quantization bit rate, pixel size and shift from optical axis. The correlation filter has proved its excellent performance and higher precision than classical correlation and joint transform correlator (JTC). Moreover, arrangement of multi-object reference images leads to 10-channel correlation signals, as sharply marked as those of a single channel. This experiment result demonstrates great potential for achieving the process speed of 10000 face/s.