example13_12

IMAGE DENOISING USING BAYES THRESHOLDING OF WAVELET COEFFICIENTS 基于贝叶斯(BAYES)阈值的小波(WAVELET)图像去噪算法源代码 (IMAGE DENOISING USING BAYES THRESHOLDING OF WAVELET COEFFICIENTS Bayesian (BAYES) threshold wavelet (WAVELET) image denoising algorithm source code)

说明：  用于绘制SW模型下的磁滞回线，可以改变磁场的方向和大小，在铁磁学中常用。(Drawing hysteresis loop under SW model can change magnetic field angle and size. Commonly used in ferromagnetism)

MATLAB实现自适应滤波器仿真，包括算法的说明、自适应滤波器的原理(MATLAB realization of adaptive filter simulation, including the algorithm shows that the principle of adaptive filter)

互信息盲源分离，这基于这么一个事实，混合信号的互信息最小时，意味着信号独立。可以参考有关书籍。在google里面，搜索mutual information blind source separation.即可搜到文章。(mutual information Blind Source Separation, such a fact-based, mixed-signal information in the most hours of each other, mean signal independence. Can reference to the books. Google the inside, Search mutual information blind source separation . that article can be found.)

it is a projet of some student who upload on web

特徵粹取（feature extraction）是特徵選取（feature selection）的延伸，簡單地說，我們希望將資料群由高維度的空間中投影到低維度的空間，因此，我們必須找出一組基底向量（base）來進行線性座標轉換，使得轉換後的座標，能夠符合某一些特性。 我們可以將特徵粹取分成「包含類別資訊」和「不包含類別資訊」兩大類。包含類別資訊指的是我們已經知道哪些資料分別歸屬於哪一類；而不包含類別資訊的特徵粹取則適用於我們不知道手上的資料點分別該歸屬於哪一類，甚至連該劃分成幾類都不知道的情況。對於這兩大類資料，可以分述如下： 對於「不包含類別資訊」的資料，我們通常使用「主要分量分析」（principal component analysis），簡稱 PCA。 (Cuiqu features (feature extraction) is feature selection (feature selection) extension, simply put, we want to base the projection data the high-dimensional space to low-dimensional space, so we have to find a set of basis vectors ( base) to the linear coordinate conversion, so that after the coordinate conversion, can meet a number of features. We can feature Cuiqu into " category contains information" and " does not contain a category of information," two categories. Contains categories of information refers to what we already know what kind of information are attributed to Cuiqu features include categories of information are not applicable to information we do not know the points are in the hands of the home in which category, and even that is divided into several class do not know the situation. For these two categories of information, can be divided as follows: For information " does not include the categories of information" , we usually use the " )

插值算法，具体使用方向为高斯插值，Kriging插值可以参考(Interpolation algorithm, the specific direction of the Gaussian interpolation, Kriging interpolation can refer to)

二值图像压缩，双正交样条小波变换实例源码及解析(Binary image compression, biorthogonal spline wavelet transform source code examples and analysis)

chapter 3 m files they are usefull for analising simple routines

this package implement a b spline algorithm in 1D 2D and 3D level. the Interpolation detail could be choose as use like.