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mallatpaper
- Mallat多尺度小波变换图像边缘检测经典文章两篇。Characterization of Signals from Multiscale Edges，Singularity Detection and Processing with Wavelets
Hierarchical-Singular-Detection--
- 设计了一个新的基于小波变换的信号奇异点分步检测法，该方法的特点是根据脉冲奇异点和阶跃奇异点的不同特征分两步从信号中提取奇异点-Design a new step detection method based on wavelet transform signal singularity points, the method of characteristics is extracted from the signal in two steps according to the different
Lipschitz
- 介绍信号奇异性的lipschitz意义，很有用的一篇PDF，很适合初学者学习用-Introduction the signal singularity lipschitz significance, useful article PDF, it is suitable for beginners to learn to use
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- 介绍了小波二进制变换的基本原理 , 简述了小波变换奇异性和信号突变的关系。 基于小波变换, 给出一种结合3R 准则、 软硬阈值折衷法的奇 异信号小波检测方 法。仿真结果表明此法 既能有效地消除噪 声, 又能较好 保留奇异信号-This paper introduces the basic principle of binary wavelet transform, signal singularity and wavelet transform are briefly discussed the
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- 变频器高次谐波产生的奇异性信号使交流调速系统不能正常工作, 采用 小波包分析对奇异性信号进行识别和提取, 对系统进行抗干扰处理, 有效地抑制了高次 谐波对交流调速系统的干扰。-H igh o rder harm on ic o f inverter produces singularity s igna ,l m ake speed governor system can. t no rm a lly ope rate. W avelet packe t theoryw as app
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- 基于最大重叠离散小波谱的定义, 本文提出了一种确定分形信号局部奇异性指数的算法, 构造了一种 类似于奇异性谱的直方图, 并用之来描述信号奇异性的全局统计分布. 算法的有效性通过数字试验及在真实心率数据 中的应用得到了验证.-Based on the definition of wavelet spectrum of the maximal overlap discrete wavelet transform, we propose a novel algorithm for dete
DFKDJFKDFJD
- 本文研究了多重分形的统计物理方法,以上证综合指数长达四年的一分钟高频数据为研究 对象,计算了实际交易数据的多重分形谱及其特征参数,并确定了权重因子的取值范围。结果表 明奇异指数和相应的谱函数作为多重分形谱的重要参数,一定程度上反映了股指本身的变化范围 和高低价位出现频率的变化,然而谱函数可以预测股市趋势的断言在沪市并不成立。 关键词:统计物理 高频数据 多重分形谱 奇异指数-This paper studies the multifractal statistical physi
06094337
- When extracting discriminative features multimodal data, current methods rarely concern the data distribution. In this paper, we present an assumption that is consistent with the viewpoint of discrimination, that is, a person’s overall biomet
Intensity of stress singularity
- ABAQUS UEL 用户自定义单元，可以采用Fortran语言编写用户程序，然后利用abaqus软件调用该程序，实现二次开发，可以输出结果到文件(SUBROUTINE UEL(RHS,AMATRX,SVARS,ENERGY,NDOFEL,NRHS,NSVARS, 1 PROPS,NPROPS,COORDS,MCRD,NNODE,U,DU,V,A,JTYPE,TIME,DTIME, 2 KSTEP,KINC,JELEM,PARAMS,NDLOAD,JDLTYP,ADLMA