power_wind_dfig_det

K-L+LDA结合了K-L和LDA优点的一个算法(K-L+ LDA combination of KL and the advantages of an algorithm for LDA)

Artech House Space-Time Codes and MIMO Systems

可以实现大规模的bfgs功能，进行目标函数的最优化求解，即L-BFGS(Can achieve large scale bfgs function, the objective function is the most optimal solution, ie, L-BFGS)

CEC09年群体智能会议的测试问题的代码(CEC09-MOEA-Codes-of-Problems matlab code)

This is a MATLAB implementation of the SIFT keypoint detector and descriptor (do_gaussian: generate Gaussian scale space of input image do_diffofg: generate Difference of Gaussian (DoG) scale space do_localmax: local extrema as the potential keypoints do_extrefine: refine the keypoints by discarding the ones with low contrast and along an edge do_orientation: compute the orientation of a support region of keypoint do_descriptor: compute the descriptor of a keypoint based on image gradients. do_match: match two images based on the nearest neighbor principle and spatial consistency. do_sift: generate the SIFT descriptors for a given input image. It basically s all the functions above. )

本课件为通信专业本科学习matlab入门课件，学习简单，适用范围广并且附有实际编程例子代码。而且还有易懂的simulink仿真(The courseware for the communications matlab introductory undergraduate learning courseware, learning simple, with a wide range of application and the actual programming code examples. But also to understand the simulink)

LVQ神经网络的预测——人脸朝向识别,MATLAB的经典算法(LVQ neural network prediction- face towards the identification, MATLAB classical algorithm)

该程序针对可靠性问题进行验证，对比分析了网络中多种链接方式的可靠性，并通过绘图形象表示(The program validated for reliability issues, comparative analysis of the reliability of the network in a variety of ways of links and images represented by drawing)

vc调用matlab dll 读xls内容(vc call the matlab dll reading xls content)

t - time series y - value of series at time t w - cycle length, defined by user based on prior knowledge of time series alpha - type I error used for cofidence interval calculations. Usually set to be 0.05 which corresponds with 95 cofidence intervals(t- time series y- value of series at time t w- cycle length, defined by user based on prior knowledge of time series alpha- type I error used for cofidence interval calculations. Usually set to be 0.05 which corresponds with 95 cofidence intervals)