module

用于模拟光纤光栅(FBG)的反射特性和时延特性,特别是用于模拟各种切趾包络下光纤光栅的反射和时延特性。(Used to simulate the fiber Bragg grating (FBG) of the reflective properties and delay properties, especially for simulation of various apodization envelope under the fiber grating reflection and delay characteristics.)

simulink of laboratory session

光伏微网逆变器并网matlab/simulink仿真，仿真效果很好，mppt环节采用扰动跟踪法，锁相环部分使用s-function编译(Solar Micro Inverter Grid matlab/simulink simulation, the simulation results very well, mppt link tracking using perturbation method, phase lock loop section compiled using s-function)

首先从n个数据对象任意选择 k 个对象作为初始聚类中心；而对于所剩下其它对象，则根据它们与这些聚类中心的相似度（距离），分别将它们分配给与其最相似的（聚类中心所代表的）聚类；然后再计算每个所获新聚类的聚类中心（该聚类中所有对象的均值）；不断重复这一过程直到标准测度函数开始收敛为止。一般都采用均方差作为标准测度函数. k个聚类具有以下特点：各聚类本身尽可能的紧凑，而各聚类之间尽可能的分开。(First, a data object from the n choose k objects as initial cluster centers and for the rest of the other objects, according to their similarity with the cluster center (distance), respectively, assign them to their most similar (represented by cluster center) clustering then calculated for each cluster center received a new clustering (all objects in the cluster mean) repeats this process until the convergence criteria begin until the measure function. Standard deviation is generally used as a standard measure function. K a cluster has the following characteristics: the cluster itself as a compact, but separated as much as possible between each cluster.)

利用MATLABWebServer实现在线作图，这个资料很有用(To use MATLABWebServer online mapping, this information is useful)

说明：  单纯形法用于解决线性规划问题，网上找的，版权归原作者所有 (Simplex method linear programming problem)

Simulation of M/G/! queue with average queue size(Simulation of M/G /! Queue with average queue size)

matlab中实现DV-hop算法，无线传感网络定位算法中非测距的常用算法的简单仿真(matlab achieve DV-hop algorithm, wireless sensor network localization algorithm commonly used in Central Africa Ranging simple simulation algorithm)

自适应信号处理的经典书籍，英文版，详细介绍了各种自适应过程(Classic books, adaptive signal processing in English, details a variety of adaptive process)

Given a complex matrix X, OX=ADJPH(X) returns the complex matrix OX that is obtained from X by multiplying column vectors of X with phase factors exp(i*phi) such that the real part and the imaginary part of each column vector of OX are orthogonal and the norm of the real part is greater than or equal to the norm of the imaginary part.