pf_nav

各种调制方式的代码，包括单天线和单天线等。(Various modulation code, including single-antenna and single antenna and so on.)

33节点的配电网潮流计算程序，程序自带33节点数据(33 nodes in the power flow calculation program, the program comes with 33 node data)

完成超宽带系统中信号的生成，以及整个过程，并且统计出了误码率，并和理论之进行了比较(complete UWB system signal generation, and the entire process, and the statistics of the BER, and the theory and the comparison)

2D周期性圆柱组成的，lens的几何设计和delay的计算，使用各项同性圆柱(2D periodic cylinder’s delay)

An introduction to Support Vector Machine implementations in MATLAB (MATLAB Workshop)

Command to Line-of-Sight Guidance

信号数据预处理程序，包括低通滤波，带通滤波(Signal data preprocessor：including a low pass filter, band-pass filter)

MATLAB GUI设计学习手记（第二版）源程序 第1章 本书推荐的学习方法： 1）若您是一个MATLAB初学者，且有充裕的时间来学习GUI设计，您可以从本书的第1章开始循序渐进地学习。 2）若您是一位MATLAB初学者，且时间非常紧迫，建议您先学好第1章，然后依次学习第4章、第5章和第6章，其他章节请根据项目需要有选择性地学习。 3）若您已经掌握了MATLAB的基础语法知识，有一定的MATLAB编程基础，也请浏览一下第1章的内容，尤其是专题分析部分。然后先学习本书第4、5和6章，其他章节请根据项目需要有选择性地学习。 4）若您是一位MATLAB GUI方面的专家或老师，您可以将本书作为一本教学的参考书，本书内容全面、讲解详实、代码精炼，是不可多得的GUI宝典。 (MATLAB GUI design learning Hearts (second edition) source Chapter 1 book recommended learning methods: 1) If you are a MATLAB beginners, and there is plenty of time to learn GUI design, you can start from Chapter 1 of the book The step-by-step learning. 2) If you are a MATLAB beginners, and the time is very tight, it is recommended that you first learn to Chapter 1, followed by learning Chapter 4, Chapter 5 and Chapter 6, in other sections based on project needs selective learning . 3) If you have mastered the basic grammar of the MATLAB, the MATLAB Programming Fundamentals, please visit the Chapter 1, in particular thematic analysis section. First learning book chapters 4, 5 and 6, then the other chapters selective learning based on project needs. 4) If you are an expert or teacher of a MATLAB GUI, you can book as a teaching reference books, the book is comprehensive, explain the detailed, refined code, is a rare GUI canon.)

example of channel modeling

用matlab进行概率密度函数的非参数估计，主要有parzen窗法和kn近邻法。分别对平均分布和正态分布进行了仿真。(Non-parametric estimation of the probability density function using matlab, main the parzen window method and kn nearest neighbor method. The average distribution and normal distribution were simulated.)