Matlab-Poincare-section-program

基于matlab的图像检索，供大家学习参考。(Matlab-based image retrieval, for them to learn from the reference.)

说明：  能实现第四代移动通信系统中的关键技术MIMO-OFDM，是一个两发两收的MIMO系统(To achieve the fourth generation mobile communication system in key technology MIMO-OFDM, is a collection of two rounds of two MIMO systems)

Block Coding channel rayleigh

1） 借助MATLAB画出误差性能曲面和误差性能曲面的等值曲线； 2） 写出最陡下降法， LMS算法的计算公式（ ）； 3） 用MATLAB产生方差为0.05,均值为0白噪音S(n)，并画出其中一次实现的波形图； 4） 根据2）中的公式，并利用3）中产生的S(n)，在1）中的误差性能曲面的等值曲线上叠加画出采用最陡下降法， LMS法时H(n)的在叠代过程中的轨迹曲线。 5）用MATLAB计算并画出LMS法时 随时间n的变化曲线（对 应S(n)的某一次的一次实现）和e(n)波形；某一次实现的结果并不能从统计的角度反映实验的结果的正确性，为得到具有统计特性的实验结果，可用足够多次的实验结果的平均值作为实验的结果。用MATLAB计算并画出LMS法时J(n)的100次实验结果的平均值随时间n的变化曲线。 6）用MATLAB计算并在1）中的误差性能曲面的等值曲线上叠加画出LMS法时100次实验中的H(n)的平均值的轨迹曲线； 7）对以上实验结果给出一些你认为有价值的讨论。 （在实验中n=1,,…..N,N的取值根据实验情况确定，一般选取足够大以使算法达到基本收敛，本题作业以电子文档PDF格式提供） (1) With MATLAB to draw the contours of the error performance surface and error performance surface 2) Write down the steepest descent method, the LMS algorithm formula () 3) using MATLAB variance 0.05, mean 0 white noise S (n), and draw one to achieve the waveform diagram 4) According to the formula 2), and using 3) S (n) produced in 1), the error performance of the contours of the surfaces superimposed on draw using the steepest descent method, the LMS method is H (n) in the iterative process in the trajectory curve. 5) curve to calculate and draw the LMS method using MATLAB with time n (time corresponding to the S (n) of a first implementation) and e (n) waveform reflect a certain time to achieve results not from a statistical point of experiment the correctness of the results obtained with the experimental results of the statistical properties of the available sufficient times the average of the experimental results as a result of the experiment. Calculate and draw the LMS m)

THIS IS SINGLE MACHINE INFINITE BUS SYSTEM

说明：  实现多尺度熵的算法 多尺度熵（Multiscale entropy, MSE）将样本熵扩展到多个时间尺度，以便在时间尺度不确定时提供额外的观察视角。样本熵的问题在于它没有很好地考虑到时间序列中可能存在的不同时间尺度。为了计算不同时间尺度下信号的复杂性，Costa等人（2002,2005）提出了多尺度熵。(MultiScale Entropy There has been considerable interest in quantifying the complexity of physiologic time series, such as heart rate. However, traditional algorithms indicate higher complexity for certain pathologic processes associated with random outputs than for healthy dynamics exhibiting long-range correlations. This paradox may be due to the fact that conventional algorithms fail to account for the multiple time scales inherent in healthy physiologic dynamics. We introduce a method to calculate multiscale entropy (MSE) for complex time series. We find that MSE robustly separates healthy and pathologic groups and consistently yields higher values for simulated long-range correlated noise compared to uncorrelated noise.)

盖尔圆法进行信号源数估计，方面不错。也可应用于聚类算法。(Source number Gail round signal estimation method, good aspects. Can also be applied clustering algorithm.)

基于matlab采用匹配滤波器实现的PN码捕获与跟踪，对学习PN码捕获的朋友很有帮助(Matlab using matched filter based on the PN code acquisition and tracking, PN code acquisition in learning helpful friend)

包含随机序列生成函数和正交复指数矩阵生成函数(Contains the random sequence generating function and the orthogonal matrix of complex exponential generating function)

Music算法是一种传统的高分辨方法，借助于该方法，本程序实现了信号源的估计问题。(This program uses Music agrithm implement the function of the estimation of the number of the souces！)