pzplot

以高斯函数为载波的PPM调制解调，及于理想误码率曲线相比较的误码率曲线(Gaussian function of PPM modulation and demodulation of the carrier, and the desired BER curves compared to BER curves)

用NRTL模型，求解萘在一种离子液体中的活度系数。 求解非线性方程、非线性拟合都可以实现。 稍微对比了一下，发现还是拟合的结果好些。 Matlab源程序及结果在附件里(with NRTL model for naphthalene in an ionic liquid in the activity coefficient. Solve nonlinear equations, nonlinear fitting can be achieved. Contrast slightly for a moment and found that the fitting or better results. Matlab source and the results of the annex)

基于matlab的PID温控模拟，使用了simulink(Matlab-based simulation of PID temperature control, use the simulink)

dijkstra算法的matlab实现，验证数据采用了河北省主要城市的赋值无权网络图，并分析了单程往复式行驶的效率因素，实际应用价值高(the dijkstra algorithm matlab to achieve, verify the data used in major cities in Hebei Province network has no right of assignment, and an analysis of the efficiency of one-way reciprocating driving factors, the practical application of high value)

说明：  时频分析工具箱，还有说明和源程序。很好的东西(Time-frequency analysis toolbox, as well as notes and source code)

在matlab中编辑示波器的的文档 内含具体操作 有用(Edit oscilloscope in matlab useful document contains specific actions)

神经网络进行预测matlab，很不错，值得看看(Neural network prediction matlab, very good, worth a look)

Matlab code for Chaining Pursuit

说明：  例题运行步骤:在Matlab命令窗口将本章目录置于当前目录；在Matlab命令窗口的当前目录中打开本章目录中的M文件Exam.m；在Exam.m文件中，将待运行例题前的注释符号“ ”去掉，并保留其他例题前的注释符号“ ”；在命令窗口键入：Exam 并回车即可运行该例题。(Example run these steps: In the Matlab command window will be placed in this chapter directory the current directory in the Matlab command window to open the current directory in the directory of this chapter M files Exam.m in Exam.m file, will be run before the note symbol example &quot &quot removed and reserved comment symbol in front of the other examples, &quot &quot in the command window, type: Exam and press Enter to run the examples.)

本文是关于无功补偿器的一种控制方法，是基于模型预测控制的，本文作者有两篇关于这个问题的论文，这一篇比较详细，可以作为了解statcom的预测控制的材料。(This article is about the kind of reactive power compensation control method is based on the model predictive control, the authors have two papers on the subject, this one in more detail, can be used as material to understand statcom predictive control.)