UE_BPR.m

trithemius poly alphabetic key

KPCA 的基本思想是将数据从输入空间映射到高维特征空间,然后在特征空间利用线性主成分分析方法计算主成分。本程序是KPCA的源程序，可实现调用。对于初学者或许有帮助。(The basic idea of KPCA is to map the data from the input space to high dimensional feature space, then in the feature space using principal component analysis method to calculate the linear principal components. This program is the source KPCA can achieve call. May be helpful for beginners.)

file include model file of matlab that contains rayleigh fading environment in bpsk

code matlab solve linear equations

模态叠加法求欧拉梁的振动响应，对于初学者非常有帮助(Modal superposition method of Euler beam vibration response, very helpful for beginners)

说明：  一种用于微阵列数据降维的reliefF算法(ReliefF algorithm for dimensionality reduction of microarray data)

说明：  基于MATLAB的双线性带通滤波器的设计(MATLAB-based bilinear bandpass filter design)

用LMS算法从白噪声中提出单频正弦信号模型(LMS algorithm with white noise from the proposed single-frequency sinusoidal signal model)

MATLAB环境下实现butterworth 低通滤波器仿真(MATLAB butterworth )

解决最短路问题的MATLAB算法，只要输入邻接矩阵即可求出结果(MATLAB to solve the shortest path problem algorithm, the adjacency matrix can be obtained as long as the result of input)