draw

matlab simulations of mimo for cdma

实现FIR滤波器设计，执行代码可以进行FIR滤波功能。(FIR frighting desgion.)

说明：  meshless beam with efg with weight function

matlab离散系统仿真程序电子系课程设计(Department of Electronics, curriculum design of Matlab discrete system simulation program)

MATLAB GUI设计学习手记（第二版）源程序 第6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), the recommended way to learn the source code Chapter 6 of this book: 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.)

DICOM to NIfTI converter by Xiangrui Li

此应用程序不仅表明了基本的使用Microsoft基础类，而且也是一个起点书面申请。(This application not only demonstrates the basic use of Microsoft Foundation Classes, but also a starting point for an application in writing.)

基于多种经典参数估计算法的窄带信号源DOA估计(for narrowband signals DOA estimation Based on a variety of classic algorithms )

Matlab与VC++混合编程，用VC调用Matlab命令(Matlab and VC++ mixed programming with VC call Matlab command)

The JPEG compression scheme is divided into the following stages: 1. Transform the image into an optimal color space. 2. Adjust Aspect Ratio 16:9 3. Digitization Scheme 4:2:0. 4. Apply a Discrete Cosine Transform (DCT) to blocks of pixels, thus removing redundant image data. 5. Quantize each block of DCT coefficients using weighting functions optimized for the human eye. 6. Encode the resulting coefficients (image data) using a Huffman variable word-length algorithm to remove redundancies in the coefficients. 7. Byte Stuffing. 8. Header JFIF 9. JPG Data Store