dwh

rls递推最小二乘算法 (rls recursive least squares algorithm)

matlab file pml photonoc crystal

A program to hide a text in an image

正对电机单闭环的系统调试的matlab中simulink仿真模型(Is the single closed-loop system debugging of motor in the matlab simulink simulation model)

matlab design file for power system project

matlabFEM is fem lab progrma source code to solve equation diferential

采用CP算法求解分形维数(Using CP algorithm to solve fractal dimension)

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))

对序列，使用自相关法，和Burg法，对其进行谱估计的程序(Sequence, using the autocorrelation method and Burg method of spectral estimation procedures for its)

它通过对矩阵分解，相当于对矩阵做了正交化处理，方法我们进行信号检测信道估计等。(It can matrix factorization, the matrix made equivalent to orthogonalization processing, signal detection method we channel estimation.)