matpower2.0

Simulink建模与仿真。包含一本关于Simulink建模仿真的书，以及一个很好的课件。(Simulink modeling and simulation. Contains a book on the Simulink modeling and simulation, as well as a good courseware.)

Practical introduction to Matlab      

matlab 简易播放器，可在matlab中播放音乐(matlab music)

基于小波的纹理特征，小波四层分解，特征向量含有均值、标准差、空间频率等，共13*4个特征。(Based on texture feature of wavelet, wavelet decomposition, four layers of characteristic vector containing the mean, standard deviation, such as spatial frequency, a total of 13* 4 characteristics.)

说明：  MIMO系统的VBLAST仿真程序，请执行blast_MMSE_IC.m(VBLAST MIMO system simulation program, the Executive blast_MMSE_IC.m)

these are the important ieee papers of bidirectional dc dc converter for reneweble energy storage systems

基于saber仿真软件,是对反激变换器仿真设计的。(Flyback converter design saber-based simulation software)

层次分析法的计算,试用前要充分理解该方法的使用规则(The calculation of the analytic hierarchy process)

基于最小二乘支持向量机的短期电力负荷预测GUI界面设计，可以参考学习(the Forecasting of Short-term Power Load of GUI design.)

Among the high-complexity methods, two methods dominate the literature Kalman filtering and Mixture of Gaussians (MoG). Both have their advantages, but Kalman filtering gets slammed in every paper for leaving object trails that can t be eliminated. As this seems like a possible deal breaker for many applications, I went with MoG. Also, MoG is more robust, as it can handle multi-modal distributions. For instance, a leaf waving against a blue sky has two modes—leaf and sky. MoG can filter out both. Kalman filters effectively track a single Gaussian, and are therefore unimodal: they can filter out only leaf or sky, but usually not both.