dc_sud

以实际所测随机中子脉冲数据的自相关函数为研究对象，借助仿真实验，开展Elman神经网络对不同浓度核材料进行识别的研究。在实测数据的基础上，通过叠加随机噪声，模拟产生了不同浓度核材料的相关函数样本用于神经网络的训练与测试，实验结果表明，(Calculating the stochastic neutron pulse autocorrelation function with the actually measured data as the research object, we carry out different simulate experiments in concentration identification of varied nuclear materials using Elman neural network. Superimposing random noise on the measured data, we get correlation function samples simulating the different concentrations of nuclear material for training and testing the neural network.)

this program basically implementation of new scheduling algorithm in NS3 for LTE/4G. it is developed in ns3 which is open source platform used cpp.

说明：  包含了大多数流形学习方法的代码,有PCA,ISOMAP,LLE,HLLE(Contains the majority of manifold learning code, with PCA, ISOMAP, LLE, HLLE)

基于电流滞环的模糊PI控制的异步电动机的SIMULINK仿真代码(Fuzzy PI control hysteresis current induction motor SIMULINK simulation code)

基于帧差法的运动图像追踪,并将追踪目标框出，是图像追踪的一个简便有效的算法(motion tracking)

Optical flow or optic flow is the pattern of apparent motion of objects, surfaces, and edges in a visual scene caused by the relative motion between an observer (an eye or a camera) and the scene.[2][3] The concept of optical flow was first studied in the 1940s and ultimately published by American psychologist James J. Gibson[4] as part of his theory of affordance. Optical flow techniques such as motion detection, object segmentation, time-to-collision and focus of expansion calculations, motion compensated encoding, and stereo disparity measurement utilize this motion of the objects surfaces and edges.[5][6]

这个主要是一些图像配准的实例，为后续的图像融合做准备。(This is mainly because some instances of image registration to prepare for the subsequent image fusion.)

waveguide dispersion simulation

muestreo por la tecnica sample and hold de una señ al diente de sierra

基于迫零算法的反馈判决自适应均衡器--matlab编程 代码(Adaptive equalizer feedback judgments based on zero forcing algorithm)