TimeHistorykepplerorbit

QPSK的matlab仿真，希望对大家有所帮助(QPSK in matlab simulation, we want to help)

Model Fitting using a Gui code in matlab. using AR,ARMA,MA models

图像的置乱处理，包括了模板置乱法，幻方置乱法和图像的一个基本加密方法——4bit置换(Scrambled images, including the template scrambling method, magic squares and image scrambling method is a basic encryption method- 4bit replacement)

刘金琨教授编写的智能控制第二版的配套源程序(Professor Liu Jinkun written in intelligent control of the second version of the matching source)

matlab在工程数学方面的应用教学文档，matlab是一款功能强大的软件，可以应用于多种领域，本文档着重介绍matlab在工程数学领域的应用。(matlab engineering applications in mathematics teaching document, matlab is a powerful software that can be used in a variety of areas, this document focuses on matlab projects in the field of mathematics.)

第04讲MATLAB语言基础-数字图像处理课件-matlab语言基础，很适合做图像如理入门使用，(Digital image processing based on matlab language courseware), such as introduction to use, very suitable for image series 1)

用matlab实现了对Hindmarsh-Rose神经元模型各个参数的仿真。包括了HR神经元模型和主程序，下载即可执行。(Hindmarsh-Rose neuron is analyzed with matlab)

小波过滤数据,提取出含有噪声数据的原始信息.并且找到噪声信息.(Wavelet filter data, the original information containing the extracted noise data. Noise information and finding.)

This is my whole part of visual basic my licence project!

Learning_random.m : 随机选择样例，从（90）pool里随机选择样本，删除版本空间树的数量 activeLearning.m:根据最大熵原则,从pool里选择样本，删除版本空间树的数量 getlabel.m:根据树和测试样例，得到根据该树得到的类标 getTrees.m:从提供的大量树结构(随机生成的)中，随机挑选一定数量的树(如果该树的叶子节点无类标随机添加) RandomCreateTree_d_unbalance:根据样本点割点中的非平衡割点建造树， RandomCreateTree_d_all.m:根据所有样本点的割点建造树 randomdata.m：给定属性取值，造数据 randomselect.m:从数据中随机选择一部分作为 showTree.m:显示树的结构 test.m:给出树，测试样例，得到正确率(Learning_random.m: randomly selected sample, randomly selected sample from (90) pool the The deleted version space tree quantity activeLearning.m: selecting a sample from the pool based on the principle of maximum entropy, delete the number of version space tree getlabel.m: According to the tree and the test sample obtained according to the class standard getTrees.m the tree: from the tree structure (randomly generated), randomly selected a certain number of trees (the leaves of the tree node class marked randomly adding ) RandomCreateTree_d_unbalance: According to the sample point cut point unbalanced cut point construction tree, RandomCreateTree_d_all.m: construction of the tree randomdata.m all sample points cut point: given the value of the property, manufacturing data randomselect.m: random data Select as part showTree.m: tree structure test.m: tree, the test sample is given to get the correct rate)