Description: 计算小波分解后的能量及小波熵。里面还有OFDM信号和WPM信号的程序。-After calculating the energy of wavelet decomposition and wavelet entropy. There is also OFDM signal and the WPM signal process. Platform: |
Size: 5120 |
Author:董庭亮 |
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Description: 分为三个函数，第一个函数的功能是用于读取ecg信号，找到小波变换模极大序列；第二个函数是子程序，用于多分辨率分解，使用 A trous 算法在分解的过程中，同时给出各级的细节和概貌，它们和原数据有着同样的长度；第三个函数是函数子程序，用于多分辨率分析中的重建。-Divided into three functions, the function of the first function is used to read the ecg signal, find the wavelet transform modulus maxima sequence second function is a subroutine for use in multi-resolution decomposition, the decomposition algorithm using A' trous process, and gives details of all levels and profiles, they are the original data have the same length third function is a function subprogram, for multi-resolution analysis of the reconstruction. Platform: |
Size: 2048 |
Author:mlh |
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Description: 音频文件的一维小波分解程序自己编写的小波一维、二维信号分解和重构Matlab程序-One-dimensional audio file their written procedures for wavelet decomposition wavelet one-dimensional, two-dimensional signal decomposition and reconstruction of Matlab procedures Platform: |
Size: 2048 |
Author:吴楠 |
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Description: 小波去噪,通过对含噪信号进行四层小波分解，此处利用db3小波系列，通过仿真发现可以很好的消除信号中的噪声-Wavelet denoising, the signal through four layers of noisy wavelet decomposition, where the use db3 wavelet series, the simulation found in the well to eliminate the noise signal Platform: |
Size: 1024 |
Author:Jhon |
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Description: 小波分解用在信号识别上面。所用信号有，单载波信号和OFDM信号以及另一种多载波信号WPM。对做信号处理和识别方面的朋友会很有帮助。-Wavelet decomposition used in the signal recognition above. Signals are used, single-carrier signals and OFDM signals, and other multi-carrier signal WPM. Do signal processing and identification of areas friend would be helpful. Platform: |
Size: 342016 |
Author:董庭亮 |
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Description: 对含噪声的图像进行识别和估计，通过小波分解，在频域中完成对图像的识别，判断是椒盐噪声还是高斯噪声，并对参数的值进行估计。-Identify and estimate noisy images, through the wavelet decomposition in the frequency domain to complete the image recognition to determine the salt and pepper noise or Gaussian noise, and estimate the value of the parameter. Platform: |
Size: 287744 |
Author:peterlox |
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Description: 信号去噪的基本步骤：
（1）信号的小波分解；
（2）小波分解高频系数的阈值量化；
（3）信号的小波重构。使用分解的低频系数以及阈值量化后的高频系数进行小波重构。
-The basic steps of signal denoising:( 1) of the wavelet decomposition of signals ( 2) the high frequency coefficients of wavelet decomposition threshold quantization ( 3) the signal wavelet reconstruction. Using the decomposition of the low frequency coefficient and threshold quantization the high-frequency coefficient after wavelet reconstruction. Platform: |
Size: 5120 |
Author:周锦程 |
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Description: 流体力学相干结构 多尺度 小波分解 正确的小波变换 里面包含了关于流体力学对于相干结构的描述-Wavelet multi-scale coherent structures in fluid mechanics correct the wavelet decomposition which contains information on fluid mechanics for the description of coherent structures Platform: |
Size: 3072 |
Author:baoquan |
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Description: 主要实现小波分解编程的方法，对想要实现小波信号重构提供编程方法-Wavelet decomposition to achieve the main programming method, provided you want to achieve wavelet signal reconstruction programming Platform: |
Size: 6265856 |
Author:weiwei |
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Description: Images require substantial storage and transmission resources, thus image compression is advantageous to reduce these requirements. The report covers some background of wavelet analysis, data compression and how wavelets have been and can be used for image compression. This project aims at implementing wavelet transform for image compression. The wavelet transform is implemented using Matlab.As the wavelets provide a unique relation between time and scale components of the signal, this property makes wavelets suitable for image compression and also the efficient decomposition of signals prior to compression. Platform: |
Size: 1024 |
Author:prince |
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Description: 内含两个功能函数，分别用于实现信号的小波分解与重构-Function contains two functions were used to implement signal wavelet decomposition and reconstruction Platform: |
Size: 1024 |
Author:李用 |
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Description: 二维图像信号的去噪步骤：
（1）二维图像信号的小波分解。选择合适的小波与恰当的分解层次N，并对待压缩的二维图像信号进行N层分解计算。
（2）对分解后的每一层高频系数，选择一个恰当的阈值，并对该层高频系数进行软阈值量化处理。
（3）二维图像信号的小波重构。用小波分解后的第N层近似（低频系数）和经过阈值量化处理后的各层细节（高频系数），对二维信号进行小波重构。-Two-dimensional image signal denoising steps: (1) two-dimensional image signal wavelet decomposition. Select the appropriate wavelet decomposition level and the appropriate N, and treatment of compressed N-layer two-dimensional image signal decomposition calculations. (2) of the decomposition of high-frequency coefficients of each layer, select an appropriate threshold, and high-frequency coefficients of the layer of soft threshold quantification. (3) Wavelet two-dimensional image reconstruction. Wavelet decomposition of the first N-layer approximation (low frequency factor) and through the quantification of threshold levels after the details (high frequency coefficients), two-dimensional wavelet reconstruction signal. Platform: |
Size: 4096 |
Author:lujun |
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