MATLAB_Simulink_PID

The quantum particle swarm optimization (QPSO) applies the quantum computing theory to particle swarm optimization, and thus has the advantages of both quantum computing theory and particle swarm optimization, so it has a faster convergence rate and a more accurate convergence value.

这是信号分析应用里面一个滤波的基本程序，非常有用，供需要者学习(This is a signal analysis application of the basic procedures inside a filter is very useful for those who need to learn)

说明：  计算一系列值出现的频数，并作出极坐标图，在地理坡向中很有用(Calculated the frequency range of value occurs, and to make Polar, is useful in geographical aspect)

基于music空间谱估计算法，使用matlab m语言实现(Based on music spatial spectrum estimation algorithm, using Matlab m language implementation)

用MATLABF仿真FP腔的传输特性，包括损耗，折射率以及半径对传输特性的影响(FP transmission based on MATLAB)

face recognition by ga

调用lorentz，生产lorent的吸引子图，即吸引子生成的主程序。(Attractor map production lorent )

考虑一个信道失真了的脉冲x(t)，在均衡器的输入端由下式表示：x(t)=1/(1+(2t/T)^2) 其中1/T为符号率。该脉冲以2/T采样率被采样，而且用一个2K+1=11的强迫归零均衡器进行均衡。写一个Matlab程序来解这些迫零均衡器的系数，求出并画出这个迫零均衡器50个采样值的输出。(Considering a channel distortion of the pulse x (T), the input end of the equalizer is represented by the X (T) =1/ (1+ (2t/T) ^2). 1/T is a symbol rate. The pulse is sampled at the 2/T sampling rate and is balanced by a 2K+1=11 forced zero equalizer. A Matlab program is written to solve the coefficients of these zero forcing equalizers and to find out and draw the output of the 50 sampling values of the zero forcing equalizer.)

本文基于MATLAB/SIMULINK动态仿真环境，以实例阐述了建立脉冲编码调制通信系统仿真模型的一般方法。根据该系统的基本原理将整个模型划分为抽样﹑量化﹑编码等几个子系统，并在传输线路上加入高斯白噪声以检验该系统的传输质量和抗干扰能力。(Title Design and Simulation for PCM communication system Abstract )

粒子群优化算法能够处理例如不可导的节点传递函数或者没有梯度信息存在。(Particle swarm optimization algorithm can handle such as node can not guide the transfer function or no gradient information exists. )