BayesThresh2

蚁群算法最短路径通用Matlab程序蚁群算法动态寻路算法(Shortest path algorithm for general ant colony algorithm Matlab program Dynamic Algorithm for Route)

matlab 实验，这是上课的实验，有基本应用，适合信号。通信专业初学者入门使用( MATLAB exercises,are suit for students whose majors are signal processing ang communication)

MIT-BIH 数据库数据读取，滤波，平台为matlab(MIT-BIH database data to read, filter, matlab platform)

Ashrae模型 太阳辐射强度预测模型 任何时间和地点(Ashrae model predictive models of solar radiation intensity at any time and place)

根据频率的不同，设置不同的滤波器，包括低通、高通、带通等(Depending on the frequency set different filters, including low pass, high pass, band pass, etc.)

10 KB signal generation using matlab for new learners fo matlab and so on

基于matlab的数字计算资料，既有程序也有案例，最新最全。(This book is a survey of the numerical methods that are common to undergraduate courses in Science, Computing, Engineering and Technology. The aim is to present sufficient methods to facilitate the numerical analysis of mathematical models likely to be encountered in practice. Examples of such models include the linear equations describing the stress on girders, bridges and other civil engineering structures, the differential equations of chemical and thermal reactions, and the inferences to be drawn from observed data.)

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.)

matlab中gui界面设计的例子，鼠标点击后连成折线，很有参考价值。(matlab gui interface design in the example, even after a mouse click into the line, a good reference.)

Non-Extensive entropy with Gaussian Information Gain for identifying and classifying regular textures which contain repetitive patterns correlated over space that translates to high probabilities in the gray level co-occurrence matrix