Patton_copula_toolbox

Coding for COA_High Precision_high convergence ***Cuckoo Optimization Algorithm*** * Matlab Toolbox Ver. 1.0.1 * programmed by: "Ramin Rajabioun, 2011" This code minimizes your cost function, so don t change any part of your code.

DTW算法的程序，申请两个n*m的矩阵D、d,分别为累积距离和帧匹配距离。这里n和m为测试模版与参考模版的帧数。然后通过一个循环计算两个模版的帧匹配距离d。接下来进行动态规划，为每个格点 （i，j）都计算其三个可能的前续格点的累积距离D1，D2，D3。考虑到边界问题，有些前续格点可能不存在，因此加入一些判断条件最后利用最小值函数min()，找到三个前续格点的累积 距离作为累积距离，与当前帧的匹配距离d（i，j）相加，作为当前格点的累积距离。该计算过程一直达到格点（n，m），并将D（n，m）输出，作为模版匹配的结果。(DTW algorithm procedures, apply two n* m matrix D, d, respectively, accumulated distance and frame matching distance. Where n and m is a reference test pattern and the template frames. Then through a loop to calculate two frames template matching distance d. Next, dynamic programming, for each grid point (i, j) are calculated from the cumulative D1 before the renewal of its three possible lattice point, D2, D3. Taking into account the boundary problem, some former continued grid point may not exist, so add some conditions to determine the final use of the minimum function min (), found three former continued accumulation of grid points cumulative distance as the distance from the current frame to match the d (i, j) added, and a current cumulative distance grid. This calculation has reached the grid (n, m), and D (n, m) output, as a result of template matching.)

说明：  对空间梁单元利用MATLAB进行了编程，仅供参考(The space beam element is programmed by MATLAB, just for reference)

用C语言编写的IEEE34节点系统画图例程，用于matlab(the graghing programme of IEEE34 node system written in C, for matlab )

利用双谱分析信号的二阶非线性，检测信号的二次相位耦合(Spectral analysis of signals using two second-order nonlinear quadratic phase coupling detection signal)

根据伪随机序列理论，由混合同余法产生均匀分布的随机数，进而根据中心极限定理来产生高斯噪声。 分析所产生的均匀分布和高斯分布随机信号的均值、方差、自相关等数字特征，估计其概率密度函数并进行分析，估计其功率谱密度并进行分析。说明该高斯噪声是否符合白噪声特性。 对该高斯噪声进行FIR低通滤波，估计输出低通型限带白噪声的功率谱、相关时间等，并结合白噪声通过线性系统相关理论来进行分析。 (According to the theory of pseudo-random sequence, a uniformly distributed random numbers by mixed congruential method to generate Gaussian noise, and then according to the central limit theorem. Produce a uniform distribution of the analysis and the mean of the Gaussian distribution random signals, variance, since the digital characteristics of the correlation, the probability density function is estimated and analyzed, it is estimated that its power spectral density, and analyzed. The Gaussian noise is in line with the characteristics of white noise. FIR low pass filter of the Gaussian noise, the estimated output of low-pass type band-limited white noise power spectrum, time, etc., combined with the white noise to be analyzed by linear system theory.)

基于MATLAB，根据过往车辆磁场引起的磁场变化，识别车辆通过时刻，车辆类型(Based on MATLAB, the magnetic field caused by passing vehicles under the magnetic field changes, and identify through the moment, the types of vehicles)

用matlab编程做的《有限元法基础与程序设计》第二章的例子(finite elment anlysis matlab)

说明：  使用EEMD对故障信号进行分解，提取不同imf的能量熵，有数据可直接运行。(EEMD is used to decompose the fault signals, extract the energy entropy of different IMF, and the data can be operated directly.)

说明：  license plate recognition