CIE_MATLAB

It is tool for using classification via path reachability.

matlab编写的一个关于船舶MMG数学模型的代码.(the code is writed by mmg math model...)

SOM神经网路和DML的结合，CVPR2014文章仿真，保证分类器的Discriminative特性和SOM快速匹配特性！(the combination of the SOM neural network and the distance metric learning method)

MATLAB 神经网络用于英文字母图像和数字的识别源程序(MATLAB neural network for images and the number of letters of the alphabet to identify the source)

函数功能是基于二进制编码遗传算法的PID整定(Function function is based on the binary-coded genetic algorithms for PID tuning)

车辆电子控制系统，方便你进行汽车电子方面的开发(Vehicle electronic control system to facilitate your development of automotive electronics)

power active filter simulation

The timing_recovery_1.mdl uses Simulinks variable step solver to create a continous time QPSK signal with both carrier and symbol rate errors. This is a relativly straight forward approach, but is computationally expensive. The sescond model, timing_recovery_2Q.mdl uses a purely discrete time approach using the same fractional sample delay approach as does the receiver. This can run much faster.

KMEANSK Performs K-means clustering given a list of feature vectors and k The argument k indicates the number of clusters you want the data to be divided into. data_vecs (N*R) is the set of R dimensional feature vectors for N data points. Each row in data_vecs gives the R dimensional vector for a single data point. Each column in data_vecs refers to values for a particular feature vector for all the N data points. The output data_idxs is a N*1 vector of integers telling which cluster number a particular data point belongs to. It also outputs centroids which is a k*R matrix, where each rows gives the vector for the cluster center. If we want to segment a color image i into 5 clusters using spacial and color information, we can use this function as follows:

说明：  决策树分类程序，包含使用的数据集和运行结果(Decision tree classifier, including data sets used and running results)