LowPassFirFliter

matlab的模式识别toolbox，将它解压缩，拷贝到matlab目录下的toolbox下，声明：请不要将这个工具箱应用到商业用途上，仅作学术参考。(pattern recognition tool box. Please unzip, copy it under the directory of matlab toolbox. Announcement: Don t apply it to commercial usage, just for research reference.)

模式识别中的bayes判别分析算法，进行逐步线性回归，小波包分析提取振动信号中的特征频率。( Pattern Recognition bayes discriminant analysis algorithm, Stepwise linear regression, Wavelet packet analysis to extract vibration signal characteristic frequency.)

用经典RK方法和四阶ADAMS预测校正算法求解微分方程(Classical RK method and fourth-order predictor-corrector algorithm for solving differential equations ADAMS)

在解光学常微分方程中的打靶法。可以结合MATLAB解方程。(Optical Solutions for Ordinary Differential Equations in the shooting method. MATLAB Solution of equations can be combined.)

轨道动力学的一些有关算法，包括拉格朗日系数计算，轨道根数求解等(Some algorithms of orbital dynamics, including calculation of Lagrange coefficients, solution of orbital elements, etc.)

LVQ神经网络的分类，乳腺肿瘤诊断的神经网络实例分析(VQ neural network, the classification of breast tumor diagnosis neural network analysis)

make the epipolar line using matlab code.

pagerank的一个简单改进，用来识别核心节点。(A simple improvement of PageRank is used to identify core nodes.)

模式识别中朴素贝叶斯分类器,实习数据的良好分类技术(naive bayesian classification)

说明：  按FPE定阶的 源程序：fpe.cpp M序列：M序列.txt 白噪声：Gauss.txt 程序中先用依模型阶次递推算法估计模型的参数，再用fpe方法判断模型的阶次。 程序运行结果如下： n: 1 判断阶次FPE的值: 0.0096406 -0.481665 1.07868 n: 2 判断阶次FPE的值: 0.00875755 -0.446739 0.00498181 1.07791 0.0527289 n: 3 判断阶次FPE的值: 0.0087098 -0.459433 0.120972 -0.0569228 1.07814 0.0390757 0.116982 n: 4 判断阶次FPE的值: 0.000396884 -0.509677 0.4501 -0.200906 0.0656188 1.07991 -0.0156362 0.442989 0.0497236 n: 5 判断阶次FPE的值: 3.2095e-007 -1.18415 0.813123 -0.517862 0.34881 -0.116864 1.07999 -0.744141 0.474462 -0.253112 0.122771 n: 6 判断阶次FPE的值: 3.23349e-007 -1.14659 0.76933 -0.487651 0.329676 -0.10377 -0.00440907 1.07999 -0.703574 0.447253 -0.235282 0.113587 0.00479688 从以上结果可以看出，当n=5时，fpe值最小，所以这时的模型阶次和参数估计值为最优结果： 3.2095e-007 -1.18415 0.813123 -0.517862 0.34881 -0.116864 1.07999 -0.744141 0.474462 -0.253112 0.122771(err)