fft

提供一种求解最优哈密尔顿的算法---三边交换调整法，要求在运行jiaohuan3（三交换法）之前，给定邻接矩阵C和节点个数N，结果路径存放于R中。 bianquan.m文件给出了一个参数实例，可在命令窗口中输入bianquan,得到邻接矩阵C和节点个数N以及一个任意给出的路径R,，回车后再输入jiaohuan3,得到了最优解。 由于没有经过大量的实验，又是近似算法，对于网络比较复杂的情况，可以尝试多运行几次jiaohuan3,看是否能到进一步的优化结果。 (Provide an optimal algorithm Hamilton- trilateral exchange Adjustment Act, requiring running jiaohuan3 (c exchange) before a given adjacency matrix C and the node number N, the results of the path stored in the R in. bianquan.m document gives examples of a parameter can be in the command window, type bianquan, be the adjacency matrix C and the node number N and an arbitrary given path R,, carriage return after the input jiaohuan3, have been the optimal solution . After the absence of a large number of experiments, it is approximate algorithm, for more complex network situations, you can try to run several jiaohuan3, can look to further optimize the results.)

三维数据矩阵的中值滤波方法，采用快速实现算法(Three-dimensional data matrix median filtering method, using fast algorithm)

Beat Tracking by Dynamic Programming This page illustrates the use of the beat_* functions to implement a simple music audio beat tracker based on dynamic programming, as described in: D. Ellis Beat Tracking by Dynamic Programming J. New Music Research 36(1): 51-60, March 2007, DOI: 10.1080/09298210701653344.

ISO532B标准方法求得的响度，通过matlab代码实现(Loudness obtained by ISO532B standard method)

说明：  THIS CODE IS INTENDEED TO GET THE PLOT FOR THE SIMULATION RESULTS OF THE DFIG

说明：  本实验的目的是了解非参数估计--parzen窗估计，对数据进行Parzen窗估计和设计分类器。并分析窗口宽度h对分类的影响。(The purpose of this study is to understand the non-parametric estimation- parzen window estimation, Parzen window estimate of the data and design of classifiers. Window width h and analyzed the impact on the classification.)

MATLAB implementation of the 3GPP Spatial Channel Model

用matlab实现脉冲压缩，MTI,MTD,及TOA定位和定位精度分析，很难得的信号处理资料(Pulse compression, MTI, the MTD, and TOA positioning and positioning accuracy analysisby using matlab)

完整的OFDM仿真程序，在matlab上运行。有详细的解释。(Complete OFDM simulation program, run in matlab. A detailed explanation.)

本算法在Matlab2008b 环境下实现了立体视觉中摄像机的基础矩阵计算。包括main, sevenPoint、eightpoint 和eightpoint_norm三个函数。 main.m 是程序的入口，包括生成和读入实验数据，分别调用sevenPoint、eightpoint 和eightpoint_norm 三个函数求基础矩阵，最后绘制出最后的结果。sevenPoint.m 是用7 点法求解基础矩阵。eightpoint.m 是用8 点法求解基础矩阵，eightpoint_norm.m 是数据规格化后的8 点法求解基础矩阵。(The algorithm is implemented in Matlab2008b environment based stereo vision camera matrix calculations. Including the main, sevenPoint, eightpoint and eightpoint_norm three functions. main.m is the entry, including the generation and reading test data were calling sevenPoint, eightpoint and eightpoint_norm three fundamental matrix function evaluation, and finally draw the final result. sevenPoint.m 7 method is based on matrix. eightpoint.m 8-point method is based on matrix, eightpoint_norm.m the data after the 8-bit normalized fundamental matrix method. )