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GHM_Wavelet
说明： GHM多小波的变换与逆变换，包括预处理和后处理(GHM multi-wavelet transform and inverse transform)
- 2021-04-28 11:38:44下载
- 积分：1
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3900001
本文研究的是利用奇异性指数实现对设备状态监视和故障预警功能。首先用LabVIEW 采集传感器电信号，然后对采集到的电信
号进行小波变换得到信号包络奇异点的奇异性指数，即设备运行状态的特征值(In this research project, we use LabVIEW to do wavelet-transformation to the signal collected by sensors in order to get singularity
index from the singular points of the particular signal’s envelope. Through comparing this eigenvalue to the figures in a standard database, we can
know the functional status of the instruments. Not only the diagnoses are continuously displayed, but alarms about signs of dysfunction will also be
raised in a proper way. In other words, both the supervision of the instrument and warning of dysfunction can be achieved)
- 2012-01-31 16:35:56下载
- 积分：1
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基于整数小波变换的编码
基于提升格式的整数小波变换及其编解码( And its arranges based on the promotion form integer wavelet
transformation decodes )
- 2004-06-23 22:43:57下载
- 积分：1
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MyWaveletDenoise小波去噪
说明： 小波变换去噪方法，过滤高频低频波，C++代码(Wavelet transform denoising method, filtering high frequency low frequency wave, C ++ code)
- 2020-05-09 17:38:51下载
- 积分：1
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脉搏信号分析 pulse
脉搏信号分析
（1）设计滤波器，实现对脉搏信号的噪声抑制和基线纠漂；
（2）时域分析：波形特征检测；
（3）功率谱分析：对消噪后的信号进行功率谱分析。要求计算信号的功率谱，功率谱峰值，峰值频率。
(Pulse signal analysis (1) design the filter, to achieve the pulse signal noise suppression and baseline drift correction (2) time-domain analysis: waveform feature detection (3) power spectral analysis: noise cancellation signal after the power spectrum analysis . Require calculation of the signal power spectrum, peak power spectrum, peak frequency.)
- 2011-07-13 09:56:01下载
- 积分：1
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EZW_Matlab
对输入的二维灰值图像，先进行提升Haar小波变换，再用经典的EZW算法对小波系数进行压缩，然后反变换重构原图像。(On the importation of two-dimensional gray value of images, first upgrade the Haar wavelet transform, and then classical EZW algorithm to compress the wavelet coefficients, and then inverse transform reconstruction of the original image.)
- 2008-04-09 21:59:48下载
- 积分：1
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Fast_Algorithm_of_Edge_Detection_Based_on_Lifting_
本文通过比较第一代和第二代小波算法特点,引入二代小波提升结构的概念,提出了一种基于二代小波提升结构的快速图像边缘检测算法 对三次B样条小波基实现提升格式,通过计算大尺度下分解子图的模值和幅角来确定边缘 经过实验比较,能比经典的边缘检测算法得出更精确的边缘图像,同时通过与基于第一代小波算法的边缘检测比较,基于二代小波提升格式的边缘检测算法计算更快速,更高效。(In this paper, by comparing first-and second-generation wavelet algorithm features, the introduction of second generation wavelet to enhance the concept of structure, a second generation wavelet-based structure to enhance the rapid image edge detection algorithm on the three B-spline wavelet lifting scheme to achieve through Calculation of large-scale mold subgraph decomposition value and increase the edge angle to determine the experimental comparison, than the classical edge detection algorithm to draw a more accurate edge image, at the same time with the first generation of wavelet-based edge detection algorithm comparison, based on the Second generation wavelet lifting scheme edge detection algorithm is faster and more efficient.)
- 2008-06-23 13:18:06下载
- 积分：1
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Imagefusion
说明： 代码主要应用于图像融合的处理方面，包含Matlab在图像方面的工具箱，小波变换算法的源代码（包含多分辨率小波算法，自适应小波算法的研究）等等(Code is mainly used in image fusion processing, the image area contains Matlab toolbox, wavelet transform algorithm source code (including multi-resolution wavelet algorithm, adaptive wavelet algorithm), etc.)
- 2010-04-21 17:11:05下载
- 积分：1
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normthresh_jp
NormThresh of wavelet coefficient
- 2012-08-27 16:08:40下载
- 积分：1
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61
说明： 提出了一种结合SVD的小波变换方法，对其在外弹道测量数据中的野值剔除进行了研究。对观测数据进行小波分解，将小波分解后的近似分量和细节分量组合实现相空间重构，作为SVD方法的输入观测矩阵，根据奇异
熵增量准则，对奇异值进行筛选，根据SVD逆变换重构原信号。这一方法克服了Hankel矩阵相空间构建方法数据
端点失真问题。以小波分解后分量重构的相空间可以满足正交性，进一步提高了SVD进行数据降噪和野值检测的精度。仿真数据和试验数据处理结果证明了这一方法的有效性。(Proposed a method of combining the SVD wavelet transform its outer ballistic measurement data in excluding outliers were studied. Observational data on wavelet decomposition, wavelet decomposition of the approximate combined component and detail component to achieve the phase space reconstruction, as the input observation matrix SVD method, based on singular entropy increment standards, singular value filter, according to the inverse transform heavy SVD structure of the original signal. This approach overcomes the Hankel matrix phase space construction method data endpoint distortion. Wavelet decomposition component of reconstruction phase space satisfy orthogonality, to further improve the SVD for data noise reduction and outlier detection accuracy. Simulation data and experimental data processing results prove the effectiveness of this approach.)
- 2013-06-02 11:10:21下载
- 积分：1
