Photonic-Band-for-2_D

Space time coding in MIMO sistems

使用music算法实现和差测角，实现波束的跟踪(differential goniometric using music algorithm )

信道估计,we will assume that the receiver knows your name, i.e., it knows s (and of course x). Based on this knowledge, the receiver will estimate h using the MVU and MMSE method (for the latter it is also assumed that the variance of the noise σ2 is known at the receiver).(Channel Estimation:we will assume that the receiver knows your name, i.e., it knows s (and of course x). Based on this knowledge, the receiver will estimate h using the MVU and MMSE method (for the latter it is also assumed that the variance of the noise σ2 is known at the receiver).)

信号调制与解调信号调制与解调信号调制与解调(Modulation and demodulation signal)

alamouti simulation procedures are the key to next-generation communications technology coding

amplitude shift keying,frequency shift keying.phase shift keying,pulse amplitude modulation,pulse width modulation

此为模式识别中Parzen窗法估计概率密度函数。 全部程序流程如下： 1、读取FAMALE.TXT文件把身高或体重给数组，并求x1的样本数N1和窗宽、体宽； 2、读取MALE.TXT文件把身高或体重给数组，并求x2的样本数N2和窗宽、体宽； 3、读取Test2.txt文件把对应的身高或体重给数组A并求A的样本数M； 4、利用Parzen窗法估计概率密度函数判别男女性别； 5、对本判别的错误率进行统计。 (This is the pattern recognition Parzen window method to estimate the probability density function . All program flow is as follows : 1 , read FAMALE.TXT file to height or weight to the array, and find the number of samples x1 N1 and window width , body width 2 , read MALE.TXT file to height or weight to the array, and find the number of samples x2 N2 and window width , body width 3 , read Test2.txt file to the corresponding height or weight requirements for the array A and A is the number of samples M 4 , the use of Parzen window method to estimate the probability density function of gender discrimination 5 , determine the error rate of the statistics . )

implementation to calculate the snr of a mri signal

说明：  我写的matlab 的ar模型代码，很实用，希望对你有帮助(I wrote the ar model matlab code, very useful, want to help you)

帧间差分法进行运动目标检测，适用于对摄像头采集到的视频进行实时检测(Interframe difference method for moving object detection, real-time detection for video captured on camera)