2-Class

boost switching converter allow the transformation of DC energy to choped energy

卡尔曼滤波算法的一网打尽，包括各种实现的matlab代码(Kalman filter algorithm a clean sweep, including implementation of the matlab code)

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))

本书从MATLAB仿真角度系统地介绍了PID控制的基本理论、基本方法和应用技术，是作者多年来从事控制系统教学和科研工作的结晶，同时融入了国内外同行近年来所取得的新成果。? (MATLAB simulation system from the perspective of the book introduces the basic theory of PID control, the basic method and application technology, is a system of control for many years in the crystallization of teaching and research work, taking into the domestic counterparts in recent years, new results obtained . ?)

武汉理工大学matlab课程设计 信号调制(wuhan university of technology )

说明：  基于线性矩阵不等式的H无穷车辆横向控制matlab仿真(Matlab simulation of H-infinite vehicle lateral control based on linear matrix inequality)

FBG反射谱，要用的人会非常需要，需要的人可以看看，很不错的(FBG id1=fopen( lambdaCMT.txt , wt ) fid2=fopen( rhoCMT.txt , wt ) f1=inline( -i.*delta.*y1-k.*y2 , t , lambda , wk , delta , k , y1 , y2 ) f2=inline( -k.*y1+i.*delta.*y2 , t , lambda , wk , delta , k , y1 , y2 ) lambda=1547 while lambda<1552 t0=-501426 h=2.0057e+003 n=500 y1=1 y2=0 )

字典树的基本功能是用来查询某个单词（前缀）在所有单词中出现次数的一种数据结构，它的插入和查询复杂度都为O(len),Len为单词（前缀）长度，但是它的空间复杂度却非常高，如果字符集是26个字母，那每个节点的度就有26个，典型的以空间换时间结构。(The basic function of the dictionary tree data structure is used to query a number of times a word (prefix) appears in all the words, which insertion and query complexity are O (len), Len is a word (prefix) length, but its space complexity is very high, if the character set is 26 letters, and that the degree of each node will have 26, the typical structure of space for time.)

SEP: A Stable Election Protocol for clustered heterogeneous wireless sensor networks

eeglab for eeg analysis