MATLAB

QAM的蒙特卡洛仿真QAM的蒙特卡洛仿真QAM的蒙特卡洛仿真.(QAM的蒙特卡洛仿真.)

用matlab实现的动态矩阵仿真程序，学预测控制的朋友可以看看啊(Achieved with dynamic matrix matlab simulation program, predictive control school friends can take a look at ah)

使用id3决策树建立学生信息管理系统，对学生成绩按照籍贯、院系、科目等分类成不及格、及格、良好、优秀(Id3 decision tree with the establishment of student information management system, according to origin of student achievement, faculty, courses, etc. and to not pass, pass, good, excellent)

1.采用C均值聚类算法对男女生样本数据中的身高、体重2个特征进行聚类分析，考察不同的类别初始值以及类别数对聚类结果的影响，并以友好的方式图示化结果。 2.采用分级聚类算法对男女生样本数据进行聚类分析。分别尝试采用身高，体重，喜欢数学，喜欢文学，喜欢运动，喜欢模式识别共6个特征，以及身高，体重2个特征进行聚类，对比聚类结果，并以友好的方式图示化结果 (1. The use of C means clustering algorithm on sample data for boys and girls in the height, weight 2 characterized in cluster analysis to investigate the initial values of the different categories and the effect on the number of classes of the clustering result, and in a friendly way of illustration result. 2. Using hierarchical clustering algorithm to male and female students sample data clustering analysis. Try both using height, weight, like math, like literature, like sports, like pattern recognition feature a total of six, as well as height, weight, two features clustering, comparing clustering results, and in a friendly way of illustration of the results)

本程序用matlab仿真卫星及轨道，希望对大家的学习有所帮助(This procedure simulation using matlab and satellite orbit, and they hope to be helpful to study the U.S.)

neural network similation fot load flow studies

which gives the DC-DC boost converter explanation

IMAGE SOURCE CODING & DECODING In This code The Coding Technique Used Is Huffman Coding Data Input Is A Gray Image The Symbols Are The Intensity Levels Of The Pixels (256 Intensity)

说明：  Expert PID Controller，Fuzzy Tunning PID Control，ingle Neural Adaptive PID Controller(Expert PID Controller, Fuzzy Tunning PID Control, ingle Neural Adaptive PID Controller)

the noise deteriorates the interpolation performance in digital images, it is effective to employ denoising prior to the interpolation. In this paper, we propose a novel interpolation framework in which denoising and image sharpening methods are embedded. In the proposed framework, the image is first decomposed using the bilateral filter into the detail and base layers which represent the small and large scale features, respectively. The detail layer is adaptively smoothed to suppress the noise before interpolation and an edge-preserving interpolation method is applied to both layers. Finally, the high resolution image is obtained by combining the base and detail layers. Experimental results show that the proposed algorithm outperforms the conventional methods