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小渡变换

小渡变换的相关文献在2001年到2017年内共计75篇,主要集中在自动化技术、计算机技术、无线电电子学、电信技术、电工技术 等领域,其中期刊论文75篇、专利文献95846篇;相关期刊54种,包括榆林学院学报、中国高新技术企业、天津职业院校联合学报等; 小渡变换的相关文献由219位作者贡献,包括杨洁明、王平、靳雁艳等。

小渡变换—发文量

期刊论文>

论文:75 占比:0.08%

专利文献>

论文:95846 占比:99.92%

总计:95921篇

小渡变换—发文趋势图

小渡变换

-研究学者

  • 杨洁明
  • 王平
  • 靳雁艳
  • 万洪晓
  • 乔闹生
  • 于慧伶
  • 于晓波
  • 于瑞琴
  • 于超
  • 于飞
  • 期刊论文
  • 专利文献

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    • 荣雅君; 林飞飞; 张志鑫; 焦晋荣; 张顺
    • 摘要: Voltage level of UHV transmission line is high,the structure is complex,and fault signal contains abundant transient components,so for fault signal being discontinuous or containing abrupt change,the piecewise Prony method has higher calculation accuracy and the noise resistance than the traditional Prony method.This paper analyzes the existing piecewise Prony method based on the mean square relative error (MSRE),which has the defects that the piecewise results are not entirely accurate and being affected by noise seriously,and the piecewise Prony method based on wavelet transform is proposed.The proposed algorithm is not affected by noise and has high calculation speed.This paper used wavelet transform to process the signal containing different noise signals and to detect the mutation point and segmenting the signal,and ideal piecewise results are obtained.The relationship of each section parameters of piecewise Prony algorithm is analyzed and calculated.For UHV transmission lines with parallel reactor the improved piecewise Prony algorithm is used for instantaneous fault and permanent fault signal analysis,and the voltage transient component is extracted.The fault properties of the UHV transmission line with shunt reactor fault are effectively distinguished.%本文在分析现有的基于相对均方误差的分段Prony算法受噪声干扰严重、分段不准确的基础上,提出了基于小波变换的分段Prony算法,该分段方法抗干扰能力强、计算速度快.文中对加入不同信噪比噪声的信号使用小波变换检测突变点对信号进行分段,得到较理想的分段结果,并对分段Prony算法各个子段之间参数关系进行分析和计算.同时针对带并联电抗器的特高压输电线路故障相恢复电压的特点,利用改进的分段Prony算法分别对发生瞬时性故障和永久性故障的故障相电压信号进行分析,提取出电压暂态分量,有效地区分出带并联电抗器的特高压输电线路的故障性质.
    • 景皓; 庞先海; 李晓峰; 孙中记
    • 摘要: 对近年来电网发展和研究的热门话题之一:电能质量扰动识别分类系统进行研究.识别分类系统使用小渡变换方法对扰动电压信号进行特征提取,之后收入由支持向量机建立的识别系统中.相对小波能量只能表达总分解层信号能量中各层信号能量的比例,对于电能质量扰动信号的检测不能直接使用信息熵公式.因此引入加权算子以改进相对小渡能量,加权算子对电能扰动特征进行放大,实时反映电能扰动特征.针对使用支持向量机建立电能质量扰动识别系统时会由于扰动信号特征向量维度高、数据庞大等问题,提出一种基于混合核函数的LSSVM建立电能质量扰动识别系统.选取RBF核函数和Polynomial核函数分别作为局部以及全局核函数,构造混合核函数,提高系统泛化能力.使用PSO优化算法对LSSVM分类器进行分类,提高分类器的识别精度等性能.最后通过实验验证研究的电能质量扰动识别分类系统的识别性能.
    • 尹金和; 齐咏生; 李志林; 闫泽峰
    • 摘要: 飞灰含碳量是影响锅炉热效率的一个重要因素,但由于电站锅炉机理复杂,很难建立能够用于飞灰含碳量实时预测和控制的机理模型.为此,将小波分析与支持向量机(SVM)算法相结合,提出基于小波SVM的飞灰合碳量预测模型.该方法可较好实现数据去噪和样本预处理,对因变量飞灰含碳量有较好预测能力,通过对样本自动筛选,实现预测模型自适应更新.最后,采用大型四角切圆燃煤锅炉热态实炉试验的运行数据对该算法进行了验证,并与神经网络预测模型进行了比较,结果显示提出的方法预测精度更高、效果更好.
    • 赵志强; 郑国维; 沈巍; 廖程
    • 摘要: The full analysis on the pulse wave is in the collection of the pulse wave signal in the signal containing a small amount of noise and more clear, however vulnerable to a variety of the influence of interference, so that the extracted pulse wave contains a lot of noise, thus loweringnoise handling is particularly necessary.At the same time, pulse wave contains human physiological and pathological information, different people will exhibit different characteristics, can be seen to determine the characteristic point of the pulse wave analysis of human physiological health makes sense.Method for signal denoising using wavelet transform and multi-resolution analysis, the method in the time domain and frequency domain can characterize the local signal information, and has a self-adaptive signal.The use of a the extremum method to determine the peak point of the pulse wave, then determined based on the peak point out the location of the other features, the experiment proved that this method can increase the detection rate of feature points.%对脉搏波的完全分析是建立在含有少量噪声且较为清晰的脉搏波信号中,然而在采集脉搏波信号时容易受到多种干扰的影响,使其提取出来的脉搏波含有大量的噪声,因此降噪处理显得尤为必要.同时,脉搏波中含有人体生理病理信息,不同的人将表现为不同的特征,可以看出确定脉搏波特征点对于分析人体生理健康很有意义.针对信号去噪问题采用小波变换和多分辨率分析的方法,该方法在时城和频域都能表征信号局部信息的能力,且具有对信号具有自适应性.运用扳值法确定出脉搏渡的峰值点,然后再根据峰值点确定出其他特征点的位置,实验证明该方法能够增加特征点的检出率.
    • 黄静; 欧凤霞
    • 摘要: 通过离散小波变换滤波层对医疗检测信号进行同步分解,并将分解量与卡尔曼滤波算法相融合,从而得到医疗检测信号的最优估计.
    • 罗鸣; 王允彬; 顾海宝
    • 摘要: 提出一种基于小波变换和模糊专家系统的暂态电能质量扰动辨识方法,利用小波变换优良的时频性和快速的Mallt算法对信号进行检测,提取电压变化幅值和持续时间等为特征量。将获取的特征量输入模糊专家系统进行电能质量扰动辨识的研究。结果表明,该方法能有效区分各类暂态电能质量扰动。
    • 李靖
    • 摘要: An edge detection algorithm based on the wavelet domain image fusion is put forward in view of the problems in multi - focus analysis and lossy image analysis difficult to advance complete edge information. Based on multiresolution analysis of wavelet transform, the theory of image fusion and enhancement is applied, to maximize the information amount of wavelet sub - band edge. Then, the classic Canny operator edge detection algorithm is used in final image edge detection%针对多聚焦度分析和部分有损图像分析中难以提前完整边缘信息的问题,提出了一种基于小波域图像融合的边缘检测算法。它是在小波变换多分辨率分析的基础上,运用图像融合及图像增强理论,使得小波子带边缘信息量最大化,再运用经典的Canny算子边缘检测算法最终实现图像边缘的检测。
    • 辛月; 姜延书
    • 摘要: 本文以目前市场运行良好的LME期铜价格作为研究对象,运用小波分析模型,绘制期铜价格小波变换幅值图和小波变换等值线图,发现期铜价格具有长周期波动和短周期波动两种波动过程,周期长度和周期强度均具有非对称性.利用这种周期波动特征进行长周期预测证明,预测结论与实际变化十分吻合,小波分析理论在期铜价格运行规律研究中的应用具有较好的实用性和发展前景.
    • 宋治国; 张银行; 邓小飞
    • 摘要: The image denoising experiment, using biorthogonal wavelet and applying VisuShrink thresholds and BayesShrink thresholds,is conducted to images mixed with Gaussian white noise through the hard threshold function and the soft threshold function respectively. The results show that denoising effect of the hard VisuShrink threshold is better than that of soft VisuShrink threshold~ the denoising effect of the soft BayesShrink threshold is better than that of hard BayesShrink~and BayesShrink can have a better denoising effect only in the soft threshold function.%采用双正交小波,利用VisuShrink阈值和BayesShrink阈值,分别通过硬阈值函数和软阈值函数对混入高斯白噪声的图像进行去噪实验.结果表明,硬VisuShrink阈值的降噪效果好于软VisuShrink阈值,软BayesShrink阈值的降噪效果好于硬BayesShrink阈值,并且BayesShrink阈值只有在软阈值函数下才能取得很好的降噪效果.
    • 郭丽华; 朱元昌; 尹文龙
    • 摘要: 为提高弹道估计精度,提出了一种基于小波分析的滤波方法,滤除外测数据中AR(自回归)模型的随机误差.分析讨论了滤波过程中的几个关键问题,提出了利用基于偏自相关系数截尾检验的方法来确定分解层数,然后采用GCV(广义交叉确认)准则来确定均方差意义下最优阈值的方法.本文提出的外测数据滤波方法计算简单,不需要估计噪声的方差.仿真结果表明,该方法能有效滤除外测数据中的AR噪声.%A filter method based on wavelet analysis is proposed to reduce the random deviation of tracking data from automatic regression (AR) model to improve the accuracy of trajectory estimation. Key issues in filtering are discussed. The number of analytical layers is defined with a method based on partial self-correlated coefficient censored verification and the optimal threshold value is defined with Generalized Cross Validation (GCV). Computation of the tracking data filter is simplified as estimation of the variance of noise is no longer necessary. As shown by the result of simulation, the method effectively filters the noise of the AR model.
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