5-storey-Shear-Frame

介绍matlab入门教材，包含遗传工具箱的使用，常见的算法函数的使用说明等(Introduction matlab entry materials, including the use of genetic toolbox, common algorithmic functions to the use of descriptions)

cdma2000系统上行链路simulink仿真程序。(simulink uplink cdma2000 system simulation program.)

这是我自己调试好了的彩色图像增强的，绝对可以使用，非常好。(This is my own and tested the color image enhancement, absolutely you can use, very good.)

turbo convolution code in matlab

信号模拟，分析以及应用可以分析波形的变换，频率周期的转换等。(Ocean Wave Theory of Physical Oceanography hydrodynamic theories programming model)

说明：  对心电信号进行预处理，肌电、工频干扰、相位漂移滤除，为后续分析做准备(The ECG signal is preprocessed, and the EMG, power frequency interference and phase drift are filtered out to prepare for the subsequent analysis)

该代码演示了如何用最小二乘法识别方程参数(The code make use of least square method to identify equation parameters)

带fig界面的matlab图像处理，涉及图像缩放，旋转，加噪去噪等，使用时先点击右下角的开始，才能继续其他操作(Fig interface matlab with image processing, involves image scaling, rotation, noise denoising, etc. When you first click the lower right corner of the start in order to continue other operations)

说明：  基于P-Q分解法的潮流计算适合初学者学习程序简单易懂(PQ decomposition method based on the trend of the calculation procedure for beginners Learn easy-to-read)

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)