shudu2

能够非常清楚的看出幅值和时间的变化规律，不用再画时、频图(Can very clear indication of the amplitude and the change of time rule，Don t draw, frequency chart)

用lms分类器实现了比较准确的分类，同时给出了实验的结果。运行正确，直接调用程序即可。(Lms classifier achieved with the more accurate the classification of the experimental results are given. Running correctly, you can directly call the procedure.)

包含用lms、mse、perceptron准则函数的二类分类器(Includes use of lms, mse, perceptron criterion function of the second-class classifier)

说明：  LTE系统中接收端的turbo解码器代码(LTE system, the receiving end of turbo code decoder)

Simple implementation of the Conjugate Gradient Method

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)

用于滚动轴承微弱故障信号的诊断的方法：最小熵反卷积程序、自适应消噪法处理轴承信号、美国西储大学轴承数据处理等5个源文件(Fault diagnosis for rolling bearing weak signal approach: minimum entropy deconvolution procedure, adaptive noise cancellation treatment bearing signals, Case Western Reserve University, United States bearing data processing five source files)

This program was to recognize number plate region only from an image.

Matlab Simulation FilesMatlab Simulation Files(Matlab Simulation Files)

Histogram of Oriented Gradient toolbox, can be used for object detection and object recognition. This code is not for commercial purpose.