gettransfer

用MATLAB的SMULINK 实现的模糊算法，用于温度控制，可以直接运行，参数已经调整好(To achieve the SMULINK with MATLAB fuzzy algorithm, for temperature control, can be directly run, the parameters have been adjusted)

读入任意大小的图像，实现长和宽上的比例缩放,matlab 图像预处理处理中有用的小程序(imread a image and resize the size of the image)

说明：  基于RlS（递归式最小均方）自适应滤波算法的C程序的仿真代码(Adaptive filtering algorithm based RlS C program simulation code)

雨流计数和疲劳寿命估算,用于统计自己获取的信号，得到载荷谱，进行疲劳计算(Rain flow count and fatigue life estimate, used to calculate the signal obtained by their own, get the load spectrum, fatigue calculation)

active power filter without any correction matlab simulink file

matlab仿真卷积码与理论值的区别以及误码率的仿真(matlab simulation convolutional codes with the theoretical value of the difference between the simulation and the error rate)

这是一个关于K均值的聚类算法希望对大家有用(This is a study on K-means clustering algorithm to all of us hope that useful)

说明：  标准25节点psat动态模型，包含模型描述以及simulink下搭建的模型(Standard 25 node psat dynamic model, including model descriptions and model structures under simulink)

该代码用以仿真小球弹跳。没有考虑水平摩擦力，空气阻力等内容。(code for the simulation of small bouncing ball. Not considering the level of friction, air resistance and so forth.)

用Parzen窗法或者kn近邻法估计概率密度函数，得出贝叶斯分类器，对测试样本进行测试，比较与参数估计基础上得到的分类器和分类性能的差别.2． 同时采用身高和体重数据作为特征，用Fisher线性判别方法求分类器，将该分类器应用到训练和测试样本，考察训练和测试错误情况。将训练样本和求得的决策边界画到图上，同时把以往用Bayes方法求得的分类器也画到图上，比较结果的异同。3．选择上述或以前实验的任意一种方法，用留一法在训练集上估计错误率，与在测试集上得到的错误率进行比较。(Use Parzen Windows method or the kn neighbor method estimated probability density function, draw the bayes classifier, to test sample to test, and the parameter estimation is based on the classifier and get the difference of classification performance. 2. At the same time the height and weight data as the characteristic, with Fisher identification method for linear classifier, and the application of the classifier to training and test sample, investigation and test training error condition. Will the training sample and utility of decision on the drawing boundary paint, and at the same time before the Bayes method with optimal classifier also paint chart, the result of the comparison of the similarities and differences. 3. Select the above or before any a kind of method of experiment, with a method for training set in the estimation error rates, and on the test set get error rates are compared.)