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使用MATLAB创建GUI界面，对图像进行相关处理，例如：几何变换、滤波、加燥等。(Use MATLAB to create a GUI interface for image-related processing, such as: geometric transformations, filtering, plus dry and so on.)

一个基于matlab的GSO(群搜索)寻优算法例程，通过修改适应度函数可以完成不同的寻优任务，可用于开发改进算法或与其他智能优化算法进行对比。(A matlab-based GSO (group search) algorithm optimization routines, by modifying the fitness function optimization can perform different tasks that can be used to develop improved algorithms or other optimization algorithms and intelligent comparison.)

计算高精度光流的源代码，可运行，可用于进一步研究之用。。(compute optical flow use a new method。。)

说明：  基于灰色系统的预测，内涵数列预测和较难实现的包络预测(Prediction based on gray system, meaning the number of columns predictable and difficult to achieve the envelope prediction)

分析比较了KF,EKF,PF等几种非线性滤波方法，很强悍的。(Comparison of the KF, EKF, PF, etc. Some non-linear filtering method, very powerful.)

语音特征参数CFCC的提取代码，原创作品。matlab程序，含参考文献及毕业论文，参考价值比较大吧(CFCC speech feature parameter extraction code, original works. matlab procedures, including references and thesis, the reference value is relatively large bar)

y_compare= 1.0954 1.1832 1.2649 1.3416 1.4142 1.4833 1.5492 1.6125 1.6734 1.7321 1.0954 1.1832 1.2649 1.3416 1.4142 1.4832 1.5492 1.6125 1.6733 1.7321 var_y=2.1742e-010 精度再上一个层次(三阶代数精度) (y_compare = 1.0954 1.1832 1.2649 1.3416 1. 4142 1.4833 1.5492 1.6125 1.6734 1.7321 1.0954 1.1832 1.2649 1.3416 1.4142 1.4832 1.5492 1.61 25 1.6733 1.7321 var_y = 2.1742e-010 precision on a level again ( Third-order algebraic precision))

自己编写的一个大批量不同类别数据录入程序，并且为防止因为数据量太大导致程序运行缓慢，将其改写成分批小规模数据。方便了大规模数据处理慢带来的各种不变。(I have written a large quantities of different types of data entry procedures, and because the amount of data in order to prevent too much causes the program to run slowly, be rewritten into small batches of data. Facilitate the large-scale data processing slow and the various unchanged.)

video transmission throgh MIMO testbed

Myplotyy情节不同的数据集具有共同的X轴使用一个数字，但个别的Y轴。 每一个曲线（Y轴）的属性可单独调整，为线性或对数尺度，正常或反向规模，置信区间等，颜色，曲线标签，... 见截图和运行示例“myplotyy_example.m”在zip文件中。 (Myplotyy plots different data sets with a common x-axis but using individual y-axes in one figure. The properties of every curve (y-axis) can be individually adjusted, such as linear or logarithmic scale, normal or reverse scale, confidence intervals, colors, curve labeling, ... See screenshot and run the example "myplotyy_example.m" included in the zip-file. )