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一维信号小波分解与重构的VC++源程序
- 这是一个使用VC++编写的“一维信号小波分解与重构的VC++源程序”，请站长检查-It is a preparation of the VC "one-dimensional wavelet decomposition and reconstruction VC source", please check station
work
- MATLAB环境下，一维小波分解并提取细节系数和近似系数，再加小波包分解信号-MATLAB environment, the one-dimensional wavelet decomposition and extract detail coefficients and approximation coefficients of wavelet packet decomposition of signal plus
work
- 有小波分解求小波熵，还有小波包技术求解信号特征，适应与分析脑电信号特征-Seeking a wavelet decomposition wavelet entropy, and wavelet packets technique to solve the signal characteristics, and analysis of EEG characteristics of adaptation
signalwaveletdecopositon
- 一维信号的小波分解重构,其中matlat的源代码是对序列做了扩展的-One-dimensional wavelet signal decomposition and reconstruction, in which the source code matlat is extended sequences done
wavelet_max
- 小波模极大值原理在图像边缘提取和信号奇异点检测中的应用-Wavelet Modulus Maxima Principle in Image Edge Detection and Signal Singularity Detection
a2
- 传统小波阈值去噪法 小波阈值收缩法去噪的主要依据是：小波变换特别是正交小波变换具有很强的去数据相关性，它能够使图像的能量在小波域集中在一些大的小波系数中；而噪声的能量却分布于整个小波域内，因此，经小波分解后，图像的小波系数幅值要大于噪声的系数幅值，可以认为，幅值比较大的小波系数一般以图像信号为主，而幅值比较小的小波系数在很大程度上是噪声。于是采用阈值的办法可以把信号系数保留，而使大部分噪声系数减少至零[-Study on Algorithm of Image Denosing Based o
waveleseriestthreshoding
- 使用matlab的小波分解和重建函数对24位的ADC采样数据进行小波变换和去噪，去噪使用阈值算法，阈值的选取具体使用了6种方法进行对比，对于不同信号其效果是不同的！把去噪后的信号和原始信号放在一个图中，使用不同颜色的曲线进行对比，效果可以很直观的表现。-Using matlab wavelet decomposition and reconstruction of the function for 24-bit ADC sampling data wavelet transform and de
Wavelet
- 一维信号离散小波分解与重构的VC程序，很经典的一个-One-dimensional discrete wavelet signal decomposition and reconstruction of the VC process, it is the classic one
d5sym
- 这是对一维信号进行五层小波分解，然后分别把不同层数的细节分量和近似分量重组这个信号。这样有除噪和最大程度提取信号能量的效果。-This is a five-story one-dimensional wavelet decomposition of signals, and then the details of each component of different layers and approximate quantity of restructuring the signal. In
wave
- 小波分层阈值去噪，用sym4小波对图像信号进行3层小波分解-On Wavelet threshold denoising using wavelet image signal sym4 3-layer wavelet decomposition
waveletsingularitydetectionsigna
- 采用2进小波对1维信号的奇异点进行检测。小波模极大值位置就是奇异点的位置-A 2 into 1-dimensional wavelet singularity detection signal. Wavelet Modulus Maxima location is the location of singular points
waveletDB4PRO
- 在理解了离散小波变换的基本原理和算法的基础上，通过设计VC程序对简单的一维信号进行小波分解系数；再通过改变分解得到的各层高频系数进行信号的小波重构达到消噪的目的-Understand the discrete wavelet transform in the fundamental principles and algorithms, based on the VC program by designing a simple one-dimensional signal wavelet coef
xiaoboquzaofenxi
- 小波去噪分析，一维信号小波分解，消噪处理，重构-Analysis of wavelet denoising
xiaoboshang
- 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.
wavelet-decomposion
- 对信号进行小波分析，小波分解，小波重构,小波分析法滤波的步骤程序。-The signal analysis, wavelet decomposition, wavelet reconstruction, wavelet analysis filtering step process.
remove-noise-by-wavelet-transform
- 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
wavelet-image
- 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-dimensiona
matlab小波分解时频分析
- 传统的傅立叶变化只能分析时域、频域图，而小波变化能进行时频分析，对信号进行更好的处理。(The traditional Fourier transform can only analyze the time domain and frequency domain diagram, while the wavelet transform can carry on the time-frequency analysis and better deal with the signal.)
小波分解
- 小波分解，将信号分解成高频信号和低频信号进行分析(Wavelet decomposition)
小波分析模极大值法
- 对信号波形进行小波变换并分解，提取模极大值，最后进行信号重构。(Wavelet transform and decompose the signal waveform, extract the maximum value of the modulus, and finally reconstruct the signal.)