bilinearFilter.m

压缩包里面有四个程序：在matlab中对图像进行过滤操作和频率操作，和函数的变换(Compressed inside four programs: the transformation of image filtering operation and the frequency of operation, and function in matlab)

实现聚类K均值算法： K均值算法：给定类的个数K，将n个对象分到K个类中去，使得类内对象之间的相似性最大，而类之间的相似性最小。 缺点：产生类的大小相差不会很大，对于脏数据很敏感。 改进的算法：k—medoids 方法。这儿选取一个对象叫做mediod来代替上面的中心 的作用，这样的一个medoid就标识了这个类。步骤： 1，任意选取K个对象作为medoids（O1,O2,…Oi…Ok）。 以下是循环的： 2，将余下的对象分到各个类中去（根据与medoid最相近的原则）； 3，对于每个类（Oi）中，顺序选取一个Or，计算用Or代替Oi后的消耗—E（Or）。选择E最小的那个Or来代替Oi。这样K个medoids就改变了，下面就再转到2。 4，这样循环直到K个medoids固定下来。 这种算法对于脏数据和异常数据不敏感，但计算量显然要比K均值要大，一般只适合小数据量。(achieving K-mean clustering algorithms : K-means algorithm : given the number of Class K, n will be assigned to target K to 000 category, making target category of the similarity between the largest category of the similarity between the smallest. Disadvantages : class size have no great difference for dirty data is very sensitive. Improved algorithms : k-medoids methods. Here a selection of objects called mediod to replace the center of the above, the logo on a medoid this category. Steps : 1, arbitrary selection of objects as K medoids (O1, O2, Ok ... ... Oi). Following is a cycle : 2, the remaining targets assigned to each category (in accordance with the closest medoid principle); 3, for each category (Oi), the order of selection of a Or, calculated Oi Or replace the consumption-E (Or))

matlab coade source for smart antenna for the simutalion of smart antenna in matlab

四阶经典R-K方法的Matlab程序和newton的matlab程序的实现(Matlab program to achieve the classic fourth-order RK method and newton s matlab program)

加入白噪声的音频水印程序，采用3级小波分解，将随机序列嵌入到低频系数中(Adding white noise of the audio watermarking procedure for the three wavelet decomposition, the random sequence is embedded into the low frequency coefficient)

matlab软件中有关elman神经网络预测的程序(matlab software procedures elman neural network prediction)

用线性外推实现语音修复,得到更好特性的语音效果(realize the bandlimited signal to wideband by linear extrapolation)

压缩感知算法重建方法：凸优化算法CVX。此方法构建具有很好的稳定性。(Compressed sensing algorithm reconstruction methods: convex optimization algorithm CVX. This method has a good build stability.)

machine learning中最经典的图书(The most classic machine books learning)

循环谱估计，能画出２维图，也能在某特定循环频率下画出１维图(Cyclic spectrum estimation, can draw 2 d figure, also can draw slices under a cyclic frequency)