Trackcar

很好的一本matlab编程辅导书籍，非常实用！(Good counseling a matlab programming books, very useful!)

用db4小波分解六层：s=a6+d6+d5+d4+d3+d2+d1(db4 wavelet decomposition of six layers: s = a6+ d6+ d5+ d4+ d3+ d2+ d1)

introduction to power electronics and its applications

说明：  用遗传算法求解函数最优值，收敛速度快且不易陷入局部最优值。遗传算法是经典算法，此程序适合初学者。(A Genetic Algorithm for the optimal value function, convergence is fast and easy to fall into local optimal value. Genetic algorithm is a classical algorithm, this program suitable for beginners.)

dijkstra.m，dijkstra算法的MATLAB程序(dijkstra.m，dijkstra Algorithm in matlab)

Plotting graphics Real Gas Van der Waals using MATLAB From Jogja to World

说明：  该代码可以仿真直接扩频系统不同正弦幅度下误码率的的大小(Simulation of bit error rate of direct spread spectrum system)

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))

说明：  一些用matlab编写的经典遗传算法算例。可以用于解决许多优化问题(using Matlab to prepare some of the classic examples of genetic algorithm. Many can be used to solve optimization problems)

运动模糊角度鉴别 傅里叶变换法 直方图均衡化Radon变换(identify motionblur by fft radontransform)