Python-GUI

盲信号分离是当前信号处理研究的热点课题之一，在无线数据通信、医学、语音以及地震信号处理等领域有着广阔的应用前景。基于负熵最大的FastICA算法用于实现盲信号分离。该方法的基本思路是以非高斯信号为研究对象，在独立性假设的前提下，对多路观测信号进行盲源分离。在满足一定的条件下，能够从多路观测信号中，较好地分离出隐含的独立源信号。(Blind signal separation is the study of signal processing, one of the hot topics in wireless data communications, medical, speech and seismic signal processing and other fields have broad application prospects. Negentropy based on the largest FastICA Algorithm for Blind Signal Separation realize. The basic idea is based on non-Gaussian signal as the research object, in the independence assumptions on the multi-channel observation signal blind source separation. In meeting certain conditions, be able to multi-channel observation signal, the better to isolate the independent source signal implied.)

模拟带噪声的匀加速直线运动，数据平滑，多个smooth函数的应用，简单易懂(Simulation with the noise of the constant acceleration of linear motion, data smoothing, multiple smooth function of the application, easy to understand)

esprit是经典的DOA算法 算法运算速度优于musci(a classic algorithm for DOA using esprit)

分数傅里叶代码，包括了分数威布尔分布，让大家相互学习学习(Fractional Fu Liye code, including scores of Weibull distribution, let us learn each other)

麦克风阵语音增强中波束形成后维纳滤波的MATLAB代码(Microphone Array Speech Enhancement Beamforming MATLAB code after the Wiener filtering)

说明：  I don t know what it is

利用matlab仿真实现在不同信道下使用不同的分集算法，以及使用不同的分集数，观察信噪比和误码率的关系，得出结论，体会分级的效果(Simulation using matlab to use different channels in different sub-set algorithm, and the use of different sub-set of the number of observed signal to noise ratio and bit error rate, concluded that the effect of experience rating)

说明：  参考维基百科（https://en.wikipedia.org/wiki/Variance-based_sensitivity_analysis）的取样过程以及对应的Estimators。理论性的东西就不进行复述了，这里主要阐述用MATLAB（R2018b）对某个特定函数进行Solo indices敏感性分析的过程。大致可分为四个过程：采样，构建函数，函数输出（将样本带入函数得到输出值），计算Sobol指数（估算一阶影响指数和全局影响指数）(Sobol global sensitivity analysis)

m.file phase congruency for image processing applications

matlab code for numerical derivatives and integrals