XIAOBOFJ

此函数基于二进小波的分解、重构的图像去噪(This function is based on the dyadic wavelet decomposition, reconstruction of the image denoising)

美国著名Rice大学的小波变换工具箱，非常实用，实现了几乎所有常用的小波变换功能。(prominent American Rice University wavelet transform Toolbox, very practical, to achieve almost all commonly used wavelet transform function.)

用小波方法把脑电信号进行频段分解，并画出图形(Using wavelet method to decompose the eeg signals into frequency bands, and draw the graph)

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.)

ECG feature wavelet transform

二次小波变换的方法用于数字信号码元速率估计(wavelet transform for bitrate estimation of digital modulated signal)

多波束、波束形成、DSP实现、多波束分析(Multibeam、Multi-beam forming、Multi-beam analysis、DSP、)

图像小波变换，可以求图像小波分解系数图，阶数可以自己设定(tuxiangxiaobobianhuan)

图像融合的经典算法 IHS算法 PCA算法 加权融合算法等融合算法 程序可以直接运行 欢迎大家下载(The classical algorithm IHS algorithm PCA algorithm weighted fusion algorithm, such as image fusion fusion algorithm program can be run directly are welcome to download)

分别用Pisarenko谐波估计法、MUSIC算法和ESPRIT算法对三正弦叠加高斯白噪声信号源进行频率估计，附件中有代码说明，编译环境为matlab。(Respectively Pisarenko harmonic estimation, MUSIC algorithm and the ESPRIT algorithm superimposed on the three sine Gaussian white noise signal source for frequency estimation, in the annex to the code description, the compiler environment matlab.)