lab1

find similar faces with eigenfaces.

this programs implements the second order digital resonator.

一个三维FDTD的计算程序，比较有用，适合初学者。(A three-dimensional FDTD calculation procedures, more useful for beginners.)

说明：  matlab用GP算法求解关联维数的值。。。。。(Solving matlab correlation dimension)

说明：  Chebyshev 用切比雪夫多项式逼近已知函数 Legendre 用勒让德多项式逼近已知函数 Pade 用帕德形式的有理分式逼近已知函数 lmz 用列梅兹算法确定函数的最佳一致逼近多项式 ZJPF 求已知函数的最佳平方逼近多项式 FZZ 用傅立叶级数逼近已知的连续周期函数 DFF 离散周期数据点的傅立叶逼近 SmartBJ 用自适应分段线性法逼近已知函数 SmartBJ 用自适应样条逼近（第一类）已知函数 multifit 离散试验数据点的多项式曲线拟合 LZXEC 离散试验数据点的线性最小二乘拟合 ZJZXEC 离散试验数据点的正交多项式最小二乘拟合 (Interpolation function)

维纳滤波语音增强算法:语音增强算法的维纳滤波器，通过scalart 1996提出的实现。使用一个决策指导的方法跟踪的先验信噪比。请注意，该信号的第一0.25sec用于模型的噪声，即，它是假定的演讲之后，0.25sec开始(Wiener Filter for Noisy Speech Enhancement, implemented as proposed by Scalart 1996. Uses a decision directed method to track the a priori SNR. Note that the first 0.25sec of the signal is used to model the noise, that is, it is assumed that speech starts after that 0.25sec)

这是一个关于商人visit许多城市，怎样走法才能使距离最短的例子，采样的了退火算法的经典案例(Traveling Salesman Problem (TSP) has been an interesting problem for a l me in classical optimization techniques which are based on linear and nonlin ogramming. TSP can be described as follows: Given a numberof cities to v d their distances from all other cities know, an optimal travel route has to und so that each city is visited one and only once with the least possible dista aveled. This is a simple problem with handful of cities but becomes complica the number increases.)

说明：  噪声中正弦信号的现代法谱分析，采用了直接法、间接法、Bartlett法和Welch法，分别分析了不同窗长度、不同窗函数和不同信噪比对谱估计的影响。(Modern normal spectrum analysis of sinusoidal signal in noise adopts direct method, indirect method, Bartlett method and Welch method. The effects of different window lengths, different window functions and different signal-to-noise ratios on spectrum estimation are analyzed respectively.)

灰色系统的matlab实现程序!可以预测未来态势发展(Gray system procedures matlab realize! Can predict the future trend of development)

基于MATLAB的遗传算法解决TSP问题的程序(MATLAB-based genetic algorithm to solve TSP problems procedures)