Traveeling sales man problem solved using genetic algorithm in matlab

Power flow analysis with TCSC using Newton- Raphson method

说明：  例子群优化的一个的简单小程序，是利用matlab写的。(Swarm optimization example of a simple small program, was written by matlab.)

设计音频降噪算法，并用MATLAB仿真实现。 1）读入一段音频后添加噪声，必须包括两种不同的噪声，信噪比：0dB~10dB； 2）分别采用滑动平均滤波器，直接频域滤波，以及谱分析后设计滤波器滤波三种方法实现，并对比效果。 3）给出各种方案的设计依据、代码、频响曲线，以及输入输出对比图。(Audio noise reduction algorithm design, and use MATLAB Simulation. 1) Read after adding noise into an audio, it must include two different kinds of noise, SNR: 0dB ~ 10dB 2) respectively moving average filter directly in the frequency domain filtering, and the filter is designed to achieve three methods filter after spectral analysis and contrast. 3) Give the design basis, code, frequency response curve, and input and output comparison chart of the various programs.)

说明：  模糊控制算法 做温度跟踪控制 TS模型 matlab开发的模糊控制实例(Fuzzy Control Algorithm for Temperature Tracking Control TS Model)

陈关荣老师的《Lorenz系统族的动力学分析控制与同步》一书的电子版(Chen Guan-Rong teacher, " Lorenz Systems Family Dynamic Analysis of Control and Synchronization," a book of the electronic version of the)

Linear receiver interfaces for multiuser MIMO communications

说明：  应用计算C6环烷烃的动力学参数，例如，反应级数以及动力学常数(obtain the reaction order and kinetics constant of C6 naphthenic hydrocarbon )

排队论，讨论单窗口单队情形，两窗口单队情形。分别计算平均等待时间，平均逗留时间，平均每分钟服务的顾客人数。(Queuing theory to discuss the situation single-window single team, two windows one team situation. Calculate the average waiting time, average length of stay, the average number of customers per minute service.)

用MATLAB实现的压缩传感，线性调频脉冲压缩的Matlab程序,可以广泛的应用于数据预测及数据分析,借鉴了主成分分析算法（PCA），含噪脉冲信号进行相关检测,粒子图像分割及匹配均为自行编制的子例程。

试用时域最小平方误差准则（最小平方逆设计）设计一个具有四项系数的IIR DF的系统函数，使其在y(n)=[3,2,1]输入激励下，输出v(n)逼近d(n)=[2,0.2,0.05]。令v(-1)=v(-2)=0。求出v(n)的前8个样值与d(n)进行比较。用matlab实现了此要求。-trial at the least square error domain guidelines (minimum inverse square design) design with a four DF IIR coefficient of the system function, so in y (n) = [3,2,1] incentive to import, export v (n) approximation d (n) = [2,0.2,0.05]. So v (1) = v (2) = 0. Get v (n) of eight samples value d (n) comparisons. Using Matlab realization of this request.