radar_MATLAB_Code

自己写的编程，有关斯密特正交化，继而qr分解(Write their own programming, about Schmitt orthogonalization, then qr decomposition)

图像处理中常用的算法，均方根误差和峰值信噪比的matlab代码(Image processing algorithms commonly used, the root mean square error and peak signal to noise ratio of the matlab code)

Image Region Labeling Software

隔离型单端反激型直直变换器的Matlab/simulink仿真例程，已检测运行无误。(Isolated single-ended flyback straight converter Matlab/Simulink simulation routines, has been detected running correctly.)

PSO particle sowarm optimisatin

本模型使用matlab建模，对风机转矩控制建模，效果很好(This model uses matlab modeling, modeling of the wind turbine torque control with good results)

在MATLAB中将seg-y格式的读入，并可以进行SEG-Y与asc2的转换以及加地震道头等操作(Seg-y in the MATLAB format will be read, and can SEG-Y and asc2 the conversion and operation of additional seismic top)

ac ac regulated chopper

Signal subspace identification is a crucial first step in many hyperspectral processing algorithms such as target detection, change detection, classification, and unmixing. The identification of this subspace enables a correct dimensionality reduction, yielding gains in algorithm performance and complexity and in data storage. This paper introduces a new minimum mean square error-based approach to infer the signal subspace in hyperspectral imagery. The method, which is termed hyperspectral signal identification by minimum error, is eigen decomposition based, unsupervised, and fully automatic (i.e., it does not depend on any tuning parameters). It first estimates the signal and noise correlation matrices and then selects the subset of eigenvalues that best represents the signal subspace in the least squared error sense. State-of-the-art performance of the proposed method is illustrated by using simulated and real hyperspectral images.

高等光学仿真源程序，有助于了解光纤光学，主要是光在光纤中传播的模式分布(Higher optical simulation program to help understand fiber optics, light propagation in the fiber mode distribution)