mimo

线性代数实践及MATLAB入门 本书是根据“用软件工具推向线性代数教学”的指导思想，参照美国1992-1997国家科学基金项目ATLAST的思路，编写成的线性代数补充教材，其目的是补充我国现有教材的的缺陷。它分为两篇，第一篇介绍线件代数所用的软件工具MATLAB语言，第二篇介绍线性代数实践。本书可作为大学本科线性代数的配套教材，也可作为广大理工、经管领域教师、工程师和研究生的参考读物。(Introduction to Linear Algebra practice and matlab This book is based on the guiding ideology"use of software tools into the teaching of linear algebra," , with reference to the ATLAST ideas of U.S. National Science Foundation(1992-1997) , written as a linear algebra supplementary materials, the purpose is to supplement our existing materials defects. It is divided into two parts, the first introduces line of pieces of software tools used in algebraic MATLAB, the second introduces linear algebra practice. )

Display 3D Images Matlab三维图像显示(DICOM MR CT PET等) 2009年02月17日 MATLAB 7 (R14) 这是一个三维图像显示的Matlab实例程序。支持DICOM MR CT PET等图像格式。并且可以对每一帧进行图像处理，如直方图均衡、绘制，反色等。 (Display 3D Images Matlab three-dimensional image display (DICOM MR CT PET and so on) February 17, 2009 MATLAB 7 (R14) This is an example of three-dimensional image display of the Matlab programs. Support for DICOM MR CT PET and other image formats. And can carry out image processing for each frame such as histogram equalization, draw, color reverse.)

说明：  matlab 决策树 简单 cart算法(Matlab decision tree simple cart algorithm)

衰落信道下的盲估计研究MIMO-OFDM,ofdm子空间仿真程序(ofdm)

Qam modulation effective matlab code

System damping model in simulink by a system springs, automovile

说明：  量子粒子群算发代码，有中文注释，适合初学者编程学习。。。。。。。。。。(Quantum particle swarm algorithm code, with Chinese notes, suitable for beginners to learn programming..........)

说明：  boosting的演示文件，matlab7.0，需自己添加数据(boosting the presentations, matlab7.0, add your own data to be)

认知无线电中的波束成形MATLAB代码。可以根据拓扑众不同位置的节点调整天线的发射功率和角度。师兄博士毕业论文里的代码。希望能有帮助(Matlab code of beamformer in Cognitive Radio. it can regulate and adjust the transmitting power and angle of antenna, which belong my laboratory mate s PHD thesis. It may help you.)

本代码主要用了多标签K近邻方法（MLKNN）实现对多标签数据进行分类(This code mainly spent more than a label K-nearest neighbor method (MLKNN) to achieve the multi-label data classification)