face-detected

说明：  GMSK信号的产生，调制，首先信号通过高斯滤波器，然后进行MSK调制(GMSK signal generation, modulation, the first signal through the Gaussian filter, and then MSK modulation)

Fiber wireless communication system using matlab

matlab图像处理的书籍源码，希望能给需要的同学一定参考价值(Matlab image processing books source code, hope can give students need a certain reference value)

特别适用于初学灰色理论GM(1,1)的同学(Grey theory GM (1, 1) study)

通过matlab代码，双向PCS控制仿真，DC-DC部分采用lyeCxId定功率单环控制，DC-AC采用Udc-Q解耦控制，系统直流电压由后级DC-AC实现稳定控制，UWvKaVx参数合适(Through the matlab code, two-way PCS control simulation, DC-DC part of the lyeCxId fixed power control, Udc-Q using DC-AC decoupling control, the system DC voltage the rear stage DC-AC to achieve stable control, UWvKaVx parameters suitable)

说明：  支持向量机，评价体系，一种新的评价方法，实例学习：基于支持向量机的我国家电企业创新能力评价指标体系研究，一学便会。(SVM evaluation index system)

i want to download some codes. plz help me

CT图像重建中的代数重建工具包(AIR Tools is a MATLAB software package for tomographic reconstruction (and other imaging problems) consisting of a number of algebraic iterative reconstruction methods. The work was carried out as part of the project CSI: Computational Science in Imaging, funded by the Danish Research Council for Technology and Production Sciences, and headed by Prof. Per Christian Hansen, DTU Compute. The collaborators are DTU Compute, Dept. of Electronic Systems at Aalborg University, and MOSEK ApS. The main part of the Matlab code was written by Maria Saxild-Hansen. The core of the functions fambeamtomo, paralleltomo, and seismictomo was written by Jakob Sauer J鴕gensen.)

说明：  K-means聚类，将多个点根据各自的坐标，一定的算法分析，在matlab上可以看到聚类结果图像，帮助人们更好的分类不同的点，确定选址问题(K-means clustering, according to the coordinates of multiple points, a certain algorithm analysis, in Matlab can see the clustering results image, help people better classify different points, determine the location problem.)

基于信道的历史信息来预测不同信道的未来可用时间可以帮助CR选择一个最佳信道进行信息传递。不同的预测准则应用到周期或是随机的开关模式中。一个CR可以学习以往不同信道的模式。我们提出一个简单的分类和学习方法去检测模式的类型和收集需要的信息用于智能信道的选择。MATLAB仿真结果显示提出的方案在随机信道的随机和周期模式中都有优越的表现。随着时间的变化，新到的切换次数减少到55 ，并且延迟时间也相应减少，而吞吐量却在提高。(Prediction of future availability times of different channels based on history information helps a cognitive radio (CR) to select the best channels for control and data transmission. Different prediction rules apply to periodic and stochastic ON-OFF patterns. A CR can learn the patterns in different channels over time. We propose a simple classification and learning method to detect the pattern type and to gather the needed information for intelligent channel selection. Matlab simulations show that the proposed method outperforms opportunistic random channel selection both with stochastic and periodic channel patterns. The amount of channel switches needed over time reduces up to 55 , which reduces also the delay and increases the throughput.)