对欧姆表测量误差的进一步讨论

从分析姆表测量的全过程出发,导出了电阻测量不确定度的估计公式。     

消偏光纤陀螺的理论和实验研究

本文首次在理论上导出消偏型光纤陀螺的零漂和标度因子表达式,并得出以下两个结论:1)在使用约 40 dB偏振器时,导致陀螺漂移的主要因素是强度误差而并不是振幅误差;2)由光学标度因子与各种器件参量关系表明开环解调时陀螺的线性误差较大.试验样机证明了以上结果,并找出减小漂移的方法.     

测量噪声对波前重构精度的影响

 Hartmann-Shack波前传感器斜率测量误差是自适应光学系统中影响波前重构精度的一个主要误差来源。针对模式法波前重构算法,推导出了普遍适用的模式法波前重构误差传递系数计算公式;利用61单元自适应光学系统中的Hartmann-Shack波前传感器测量的斜率数据,验证了模式法波前重构误差传递系数计算公式的正确性。     

用偶幂级数处理Abel变换问题

本文提出了用偶幂级数代替对称分布函数,使其线积分成为递推可积,从而简化了Abel逆变换。引进权函数使本方法简单地过渡到非对称问题。对一组假想相移信号进行变换,获得了可靠的密度分布结果,并对影响变换精度的各种因素作了讨论。     

一种外场天线测试转台设计

为了满足天线在野外的测试需要,提出了一种外场天线测试转台的结构设计;该转台采用蜗轮蜗杆传动方式,可实现天线的俯仰和方位运动;文中对转台的组成进行了描述,并针对俯仰部件和方位部件的结构设计分别进行了详细说明,同时分析了转台的受力情况,对驱动力矩和惯量匹配进行了校核计算,从理论上分析了传动精度和测角精度;实际测试表明,该转台结构设计完全达到技术指标要求,能够满足天线外场测试的需要。     

真值、随机误差、系统误差的新定义

我国计量技术规范《JJF1001—1998通用计量术语及定义》对真值、随机误差和系统误差给予了新的定义,对过去的定义作了原则上的改变.本文对新定义的科学性和合理性进行了讨论,并建议在大学物理实验教学和教材中采用.     

常用激光峰值功率公式误差分析

为分析脉冲激光中常用峰值功率公式的误差,对高斯脉冲、双曲正割脉冲、洛仑兹脉冲、非对称双曲正割脉冲的常用峰值功率公式的误差进行了解析计算。结果表明：高斯脉冲、双曲正割脉冲、洛仑兹脉冲、非对称双曲正割脉冲中,常规峰值功率公式的结果与实际峰值功率的误差分别为6.3%,13.6%,22.1%,20.9%。在具体实验基础上采用数值方法分析了非常规脉冲的情形,给出了精确计算峰值功率的方法。     

高精度瑞奇-康芒检测法研究及测试距离精度影响分析

为实现高精度瑞奇-康芒法检测,利用检测系统光瞳面与被测平面镜二者间的坐标转换关系,结合最小二乘法直接对测得的系统波像差进行恢复,通过两角度检测分离由光路调整引入的离焦误差,得到更为精准的平面镜面形。分析光路中测试距离对坐标转换关系以及瑞奇角求解精度的影响,根据仿真分析结果确定实验方案。实验中采用两角度检测,对测试波前进行恢复并分离系统调整误差后,最终得到被检平面镜面形,结果峰谷(PV)值为0.182λ、均方根(RMS)值为0.0101λ,对比干涉仪直接检测结果 PV值为0.229λ、RMS值为0.013λ,PV检测精度优于λ/20,RMS检测精度优于λ/100,实验结果证明了此种面形恢复方法的有效性以及测试距离精度分析理论的正确性,从而实现了瑞奇-康芒法高精度检测。     

A framework for classification with single feature kernel matrix

In this paper, we propose a novel classification framework using single feature kernel matrix. Different from the traditional kernel matrices which make use of the whole features of samples to build the kernel matrix, this research uses features of the same dimension of any two samples to build a sub-kernel matrix and sums up all the sub-kernel matrices to get the single feature kernel matrix. We also use single feature kernel matrix to build a new SVM classifier, and adapt SMO (Sequential Minimal Optimization) algorithm to solve the problem of SVM classifier. The results of the experiments on several artificial datasets and some challenging public cancer datasets display the classification performance of the algorithm. The comparisons between our algorithm and L₂-norm SVM on the cancer datasets demonstrate that the accuracy of our algorithm is higher, and the number of support vectors selected is fewer, indicating that our proposed framework is a more practical approach.     

Intelligent reversible watermarking technique in medical images using GA and PSO

The advances in recording, editing, and broadcasting multimedia contents in digital form motivate to protect these digital contents from illegal use, such as duplication, manipulation, and redistribution. However, watermarking algorithms are designed to satisfy requirements of applications, as different applications have different concerns. We intend to design a watermarking algorithm for applications which require high embedding capacity and imperceptibility, to maintain the integrity of the host signal as well as embedded information. Reversible watermarking is a promising technique which satisfies our requirements. In this paper, we concentrate on improving the watermark capacity and reducing the perceptual degradation of an image. We investigated the Luo's [1] additive interpolation-error expansion algorithm and enhanced it by incorporating with two intelligent techniques: genetic algorithm (GA), and particle swarm optimization (PSO). Genetic algorithm is applied to exploit the correlation of image pixel values to obtain better estimation of neighboring pixel values, which results in optimal balance between information storage capacity and imperceptibility. Particle swarm optimization (intelligent technique) is also applied for the same purpose. Experimental results show that PSO and GA nearly give the same results, but GA outperforms the PSO. Experimental results also reveal that the proposed strategy outperforms the state of art works in terms of perceptual quality and watermarking payload.