fig1_21

MATLAB学习资料，感兴趣的朋友可以下载(err)

按照《双色球EXCEL全攻略》用matlab重写的双色球统计程序。(A lottery Predicting program developed with matlab.)

SAR原始数据，对初学者很有用啊！特别是用matlab读取的很方便(SAR raw data, useful for beginners! Especially matlab read very convenient)

该图片是对无线传感网络，从能量和死亡节点进行仿真验证，所用算法为改进量子遗传算法(The picture is a wireless sensor network nodes and death from energy simulation, the algorithm used to improve the quantum genetic algorithm)

this is matlab code for create admittance matrix

说明：  此程序为时频分析工具箱，在MATLAB中添加此工具箱可对信号进行时频分析，无需再自己编写程序(This program is too frequency analysis toolbox, add to this toolbox in MATLAB can signal time-frequency analysis, no longer need to write your own program)

FilterTitleOverlay字幕叠加的filter(FilterTitleOverlay subtitles superimposed filter)

这是TD算法的逆过程，首先将时间序列，划分为相邻点的短序列，当然此时的拟合误差为0，因为第一点和第二点的连线，原始点都落在线段上。将相邻两个线段连接起来，此时每条线段包含三个原始点，计算中间那个点的拟合误差。这样，所有这些三个点的线段中的中间点的拟合误差计算出来后，找出误差最小且误差小于阀值R的分段，作为第一条包含三个点的线段。 在上面的基础上，第一条分段同样的和相邻线段连接，然后计算每一条分段的拟合误差，再找出误差最小且小于阀值R的分段，作为第二个分段。依次方式循环，直到所有分段的拟合误差都小于阀值R，分段结束。 (This is the reverse process of TD algorithm, the first time series is divided into short sequences adjacent dots, of course fitting error is zero at this time, because the first and second points of connection, the original point fall line on. The two adjacent segments are connected, then each segment contains three original point, the intermediate fitting error calculated that point. Thus, after all these segments fitting error of three points in the intermediate point calculated to find the minimum error and the error is less than the threshold R segment, as the first line contains three points. Based on the above, the first segment and the adjacent line segment connecting the same, and then calculate a fitting error for each segment, and then find the smallest error and less than the threshold R segment, as the second segment . Followed by a cyclic manner until all segments fitting error is less than the threshold R, segment ends.)

在matlab环境下的有关RLS算法,多麦克风语音降噪(In the matlab environment of the RLS algorithm, multi-microphone noise reduction Voice)

data deduplication in cloud computing