Fuzzy_control

matlab 中关于RTDX的应用，含有例程，适合初学者学习(matlab on RTDX application contains routines, suitable for beginners to learn)

要求使用继电自整定方法对其实施自适应PID控制。 1、选择采样时间0.1s，把对象离散化。 2、加继电（开关）控制，测量对象的Tc,Kc。 3、利用ZIEGLER-NICHOLS 公式表，确定PID参数。 4、实现闭环控制。 5、根据调节效果，修正PID参数。 (Require the use of relay tuning methods for its implementation of the adaptive PID control. 1, select the sampling time 0.1s, the discrete objects. 2, plus relay (switch) control, measurement object Tc, Kc. 3, using ZIEGLER-NICHOLS formula table, determine the PID parameters. 4, closed loop. 5, according to moderating effect, the amendment PID parameters.)

matlab代码，低回声图像的边缘提取处理(matlab code, low-echo images of the edge extraction processing)

这个第四代移动通信中，OFDM－MIMO的例子，是vblast的仿真代码(The fourth-generation mobile communications, OFDM-MIMO example is VBLAST simulation code)

mfcc的matlab显示方法，可以直接运行(mfcc s showing by matlab)

动态系统建模与仿真第二，第四章，详细介绍MATLAB环境下的建模仿真。(Dynamic System Modeling and Simulation II, Chapter IV, details of the modeling and simulation environment MATLAB.)

Highcharts-3.0.7的样例代码，特别试用，可供各位初学者参考和使用。(Highcharts SourceCode)

如何在Simulink中搭建Sigma Delta ADC的的非理想模型MODELING BAND，已通过测试。 (In Simulink to build a Sigma Delta ADC' s non-ideal model MODELING BAND, has been tested.)

运输问题的matlab源码，欢迎大家交流：）(transport issues Matlab source, all are welcome to exchange :))

说明：  ：DBSCAN是一个基于密度的聚类算法。该算法将具有足够高密度的区域划分为簇，并可以在带有“噪声”的空间数 据库中发现任意形状的聚类。但DtLqCAN算法没有考虑非空间属性，且DBSCAN算法需扫描空间数据库中每个点的e一 邻域来寻找聚类，这使得DBSCAN算法的应用受到了一定的局限。文中提出了一种基于DBSCAN的算法，可以处理非空 间属性，同时又可以加快聚类的速度。(: DBSCAN is a density-based clustering algorithm. The algorithm has a sufficiently high density area is divided into clusters, and to be with the &quot noise&quot found in the spatial database clusters of arbitrary shape. But DtLqCAN algorithm did not consider non-spatial attributes, and spatial database DBSCAN algorithm to be scanned for each point e in the neighborhood to find a cluster, DBSCAN algorithm which makes the application subject to certain limitations. In this paper, an algorithm based on DBSCAN can handle the non-spatial attributes, can also speed up the clustering speed.)