一个好用的图像增强相关算法程序

Regression analysis using machine learning

说明：  matlab环境下的多路串口数据实时绘图显示，GUI界面。(matlab environment in real-time multi-channel serial data graphics, GUI interface.)

AWGN信道、瑞利衰落信道、多径信道条件下的OFDM信号与单载波信号的识别(AWGN channel, Rayleigh fading channels, multipath channel conditions, single-carrier OFDM signal with the signal recognition)

this paper desctibes one of new method in photovoltaic issues. nice information included

SAR-CSA算法成像(matlab)，成像效果好，有一定的参考价值(SAR-CSA image matlab)

去斜率（strech）参考信号与回波信号混频后得到中频输出信号S(t)=Aexp(j*2*pi*f0*t+phase) 其中f0与回波延时的关系为： f0=k*delay_t K为线性调频斜率，delay_t为回波延时 将s(t)采样，FFT变换即可得到目标距离与频谱的关系。 Strech 信号测距 输入混频后的中频信号（图一），经采样及FFT变换得到频谱（图二） 再根据频谱与距离的关系式R=Tcf/2B显示出距离(图三) (Go slope (strech) obtained after the reference signal and the echo signal mixer IF output signal S (t) = Aexp (j* 2* pi* f0* t+phase) f0 and echo delay relationship: f0 = k* delay_t K chirp slope, delay_t the echo delay sampling s (t), the FFT transform to the target distance spectrum of relations. Strech signal ranging input mixer IF signal (Figure 1), sampling and FFT transform spectrum (Figure 2) according the the spectrum distance relationship R = Tcf/2B shows the distance (Figure 3))

说明：  Matlab；金融计算；var计算；cvar计算 [VaR&&CVaR] VAR，CVAR详细介绍，并附带各种方法计算，matlab程序实现，仿真结果图展示。 [Matlab和金融计算] Matlab实现金融计算，并附带蒙特卡洛实现。([VaR&&CVaR] Var, cvar are introduced in detail, as well as various methods of calculation, and matlab program calculation is included, and the results are displayed in graphs. [Matlab and financial calculations] Matlab implements financial calculations with Monte Carlo implementation.)

伪随机码的模糊函数及其相关特性，用matlab仿真实现(Ambiguity function of pseudo-random code and its related properties, Simulation using matlab)

互补滤波器的程序讲解，互补滤波器的程序讲解，互补滤波器的程序讲解(Complementary filter program to explain, explain the complementary filter program, a program to explain the complementary filter)

常规的中值滤波器，在噪声的密度不是很大的情况下效果不错。但是当概率出现的概率较高时，常规的中值滤波处理后，仍然具有噪声点，并丢失了细节和边缘，效果不是很好。 自适应中值滤波器可以尽可能的保护图像中细节信息，避免图像边缘的细化或者粗化。(The conventional median filter works well when the noise density is not very large. However, when the probability of probability is high, the conventional median filter still has noise points, and the details and edges are missing. The result is not very good. The adaptive median filter can protect details in the image as far as possible and avoid thinning or coarsening of the image edges.)