PLStest

求线性方程组的迭代法，基于MATLAB开发(Linear Equations of the iterative method, based on the MATLAB development)

[自動控制] Routh-Hankel matrix數值計算工具，輸入System Function後，程式會計算Hankel singular values and vectors、Schmidt pairs等值。詳情請見英文描述。(<<singular values and vectors>> [R_G,Sigma,U,V,Us,Vs]=HANKEL3(G) computes the Routh-Hankel matrix, the Hankel singular values and vectors, the Schmidt pairs of a given proper stable system G (created with either TF, ZPK, SS, or FRD).|| Output "R_G" is the Routh-Hankel matrix. || Output "Sigma" is a matrix whose elements on the diagonal are the Hankel singular values of the given system. || Output "U" is a matrix, the ith column of which is the left singular vector corresponding to the ith singular value. || Output "V" is a matrix, the ith column of which is the right singular vector corresponding to the ith singular value. || Output "Us" and "Vs" provides the Schmidt pairs. The ith elements of Us and Vs form the Schmidt pair corresponding the ith Hankel singular value. )

罚函数法将有约束最优化问题转化为求解无约束最优化问题。在此给出罚函数法Matlab源程序(Penalty function method will be constrained optimization problem into solving unconstrained optimization problems. This gives the penalty function method in Matlab source)

雷达系统中用于计算起伏目标的检测概率，适用于Swerling I型目标。(Used to calculate the undulation target detection probability, applies Swerling I target.)

低通滤波器的源程序，计算低通阶跃高低阻抗形式，由指标来确定高低阻抗的长度(Source of low-pass filter to calculate the level of resistance in the form of low-pass step by the indicators to determine the length of high and low impedance)

This Document describes the design of cluturing Network in A WSN

用matlab的sound()函数，编辑了可以播放国歌的应用范例(A program which can play our national song)

This book is about Biomass.

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))

使用Matlab软件工具，计算经典Music算法中的RMSE数据(A way to get the RMSE of classical Music mathod with Matlab tools.)