qiujieguoch

2009 Online blind image deconvolution for astronomy 源代码，多通道反卷积处理图像，远算速度比较快(2009 Online blind image deconvolution for astronomy source code, multi-channel deconvolution process images far faster calculation)

为作业最终的仿真结果与分析 PL_free.m：free space path loss model PL_logdist.m: log-distance path loss model PL_lognorm.m: log-normal shadowing path loss model plot_PL_general.m: plot the figures itum.m: ITU M.1225 vehicular-B(120km/hr) channel model AWGN.m: create AWGN channel object(The final for the job simulation results and analysis PL_free.m: free space path loss model PL_logdist.m: log-distance path loss model PL_lognorm.m: log-normal shadowing path loss model plot_PL_general.m: plot the figures itum.m: ITU M.1225 vehicular-B (120km/hr) channel model AWGN.m: create AWGN channel object)

一种用于图像超分辨率分析的混合高斯模型算法。可实现图像方法，同时保持很好的图像边缘。(For image super-resolution algorithm for Gaussian mixture model analysis. Image method can be realized while maintaining a good edge.)

说明：  用matlab实现世界地图调用和显示，可以任意控制范围(using Matlab world map and calls, it can be arbitrary control)

AN ANN BASED APPROACH FOR OPTIMAL PLACEMENT OF DSTATCOM FOR VOLTAGE SAG MITIGATION(Voltage sag has been considered as one of the most harmful power quality problem as it may significantly affect industrial production. This paper presents an Artificial Neural Network (ANN) based approach for optimal placement of Distribution Static Compensator (DSTATCOM) to mitigate voltage sag under faults. Voltage sag under different type of short circuits has been estimated using MATLAB/SIMULINK software. Optimal location of DSTATCOM has been obtained using a feed forward neural network trained by post-fault voltage magnitude of three phases at different buses. Case studies have been performed on IEEE 14-bus system and effectiveness of proposed approach of DSTATCOM placement has been established)

mfcc 的matlab的实现，此方法在matlab上运行成功(mfcc the matlab realization this method successfully run in matlab)

genetic algorithm In the field of artificial intelligence, a genetic algorithm (GA) is a search heuristic that mimics the process of natural selection. This heuristic (also sometimes called a metaheuristic) is routinely used to generate useful solutions to optimization and search problems.[1] Genetic algorithms belong to the larger class of evolutionary algorithms (EA), which generate solutions to optimization problems using techniques inspired by natural evolution, such as inheritance, mutation, selection, and crossover.

emd分解程序,可以分解得到多个符合条件的imf分量(It is emd.)

BCH_Soft matlab files

详细介绍了Kalman滤波的理论知识，应用原理和应用环境(Kalman filter described in detail the theory of knowledge, theory and application environment application)