IEEE33

基于matlab 模拟仿真FDTD算法对印刷电路板表面的传输特性(Based on MATLAB simulation FDTD algorithm on the surface of the printed circuit board transmission characteristics)

matlab科学运算的教程,对于学习matlab的同学可以看一下(scientific computation matlab tutorials matlab for students learning to look at)

MATLAB GUI设计学习手记（第二版）源程序 第7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) Chapter 7 book recommended source 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.)

matlab编写的全息程序，主要用于计算全息以及数字再现，(matlab prepared holographic program, mainly used to calculate the hologram and digital reproduction,)

this file is a simulation of simple boost control in z_zource inverter

This is my Master Thesis for Association Rule Mining With Binary Genetic, Enjoy it

基于K均值的PSO聚类算法,D-S证据理论数据融合，有借鉴意义哦。( K-means clustering algorithm based on the PSO, D-S evidence theory data fusion, There are reference Oh.)

Restricted Boltzmann Machine with binary visible ,hidden units and GPU (CUDA) support.

NSGA2仿真实例，可用于神经网络仿真测试(NSGA is a popular non-domination based genetic algorithm for multi- objective optimization. It is a very effective algorithm but has been generally criticized for its computational complexity, lack of elitism and for choosing the optimal parameter value for sharing parameter. A modified version, NSGA- II was developed, which has a better sorting algorithm , incorporates elitism and no sharing parameter needs to be chosen a priori. NSGA-II is discussed in detail in this.)

说明：  程序中 时间结点错开了一个位子； （2）没有注意保存中间结果，程序画出的只是之后一个小时间段结果。(Staggered in time node program a seat (2) lack of attention to hold intermediate results, the program just to draw a small period of time after the results.)