hilbert

针对三个非相干QASK数字调制信号的空间谱估计程序(For three non-coherent digital modulation signals QASK spatial spectrum estimation procedure)

差集天线阵列分析\方向图、二维图、三维图(difference sets)

说明：  多变量内模模糊控制程序，将内模控制与模糊控制结合起来，实现更好的控制效果。(Multi-variable fuzzy internal model control procedures, the internal model control and fuzzy control combined to achieve a better control effect.)

本例利用小波分析检测信号中的奇异点并消除(Using wavelet analysis of signal singularity detection and elimination in)

说明：  自己练习编写的波动方程，不知道行不行，求指正，求批评(wave equation)

PSO (particle swarm optimization)

奇异值分解降噪技术，对各种信号进行处理，使用先进的MATLAB程序进行分解处理，达到理想的效果(SVD noise reduction on various signal processing, the use of advanced decomposition MATLAB processing procedures to achieve the desired results)

数学建模的教材，挺经典的，不妨一看啊啊，好吧，20字(Mathematical modeling of teaching material, very classic, might as well see ah)

to detect edge usin canny filter

实验一 双极性矩形随机信号的归一化功率谱密度一 1.1 功率谱密度简介 平稳过程的任何一个非零样本函数的持续时间为无限长，显然都不满足绝对可积和总能量有限的条件。因此，它的傅里叶变换不存在即没有频谱函数。所以我们用功率谱密度来表述其频谱特性。 随机过程的任一实现是一个确定的功率型信号。而对于任意的确定功率信号f(t)，它的功率谱密度为： 式中， 是f(t)的截短函数 对应的频谱函数。f(t)是平稳随机过程 的一个实现。而随机过程某一个实现的功率谱密度不能作为过程的功率谱密度。过程的功率谱密度应该看作是任一实现的功率谱密度的统计平均，即 虽然该式给出了平稳随机过程的功率谱密度，但我们通常都不利用这个式子来计算功率谱。我们知道，确知的非周期功率信号的自相关函数与功率谱密度是一对傅里叶变换。对于平稳随机过程，也有类似的关系，即 和 对于平稳随机过程我们通常先求出其自相关函数再利用上式求出其功率谱密度。 1.2 实验要求  1.了解平稳随机信号功率谱的概念及计算方法  2.仿真不同占空比，等概、非等概双极性矩形随机信号的归一化功率谱密度  3.分析不同信号所包含的频谱分量，有无直流分量和定时分量信息 (A pair of rectangular random experiment polarity signal sample return a nonzero function of any duration power spectral density of a 1.1 power spectral density of a stationary process Introduction of infinite length, apparently not satisfied absolutely integrable and the total energy of the limited conditions. Therefore, it is the Fourier transform of the spectrum that does not function does not exist. Therefore, we use the power spectral density to express their spectral characteristics. Any random process is a realization of a certain type signal power. For arbitrarily determined power signal f (t), its power spectral density is: wherein, is f (t) is a function corresponding to the truncated spectrum function. f (t) is a stationary random process of realization. The random process to achieve a certain power spectral density can not serve as the power spectral density of the process. Power spectral density process should be seen as a statistical average power spectral density of any r)