elman_app

QPSK调制下的信道信噪比的分析与研究，里面的仿真不错，很详细。(QPSK modulation of channel signal to noise ratio analysis and research, which the simulation well, very detailed.)

将文件扩展名改成“.m”就可以直接放在工具箱里用了 计算经验模态分解( EMD_ONLINE (On Line Empirical Mode Decomposition) computes on-line EMD IMPORTANT: EMD_ONLINE does not truly apply EMD on-line but it does AS IF. It is rather a demonstration that EMD can be applied on-line.)

用不同的窗函数设计FIR滤波器，并做出频谱图比较不同滤波器的性能差异(Window function with a different design FIR filter, and compare the spectrum to make a difference in performance filter)

给出了30个matlab智能算法案例。对于智能算法的学习者有很大的帮助。(Gives 30 matlab intelligent algorithm cases. For intelligent algorithms learners a great help.)

数据处理matlab中关于gapp算法的代码(About gapp algorithm in matlab code)

matlab 使用基本的命令介绍，包含许多基本的命令(matlab introduce some information about how to use it )

采用身高和体重数据作为特征，在正态分布假设下估计概率密度，建立最小错误率Bayes分类器，写出得到的决策规则.(Height and weight data used as the feature, under the assumption of normal distribution probability density estimation, establish Bayes minimum error rate classifier, written by the decision-making rules.)

本程序实现了在matlab环境下进行基于高阶累积量的MUSIC算法仿真(This procedure has in the matlab environment Cumulant Based MUSIC Algorithm Simulation)

二维泊肃叶流动的模拟源代码，利用格子波尔兹曼方法进行计算，计算结果如程序所示(The analog source code of the two-dimensional Poiseuille flow using lattice Boltzmann method is calculated, the calculated results of such procedures shown)

Robust Non-negative Dictionary Learning for Visual Tracking The provided codes could be either embedded into the benchmark framework of paper Online Object Tracking: A Benchmark (CVPR2013) (You can find details here: http://visual-tracking.net/) or run on individual sequence. To run the benchmark, just put the entire folder into the /trackers folder in the benchmark code base, and modify the configTrackers.m in util folder. DLT gets an AUC of 0.436, which ranks 5th among 26 in the benchmark by 19/03/2014. We don t tune parameters for single sequence in this case, all the parameters are stored in trackparam_DLT.m. To run on individual video, you need to modify the dataPath and title in run_individual.m. If you run MATLAB version after 2012, and have a CUDA compatible GPU installed, you may enjoy the fast computation speed by GPU, just set useGPU to true in trackparam_DLT.m and run_individual.m!