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关于信号处理中的自适应算法的常用算法集，希望能对相关人士有所帮助！(On signal processing algorithms commonly used set of adaptive algorithms, hoping to help the relevant parties!)

谐波恢复的ARMA建模算法(基于SVD-TLS)（张贤达《现代信号处理》）。当谐波信号为复谐波的时，该算法仍然适用。但该程序中没有给出具体的实现。(Harmonic Retrieval of ARMA modeling algorithm (based on the SVD-TLS) (Xian Tatsu Modern Signal Processing ). When the harmonic signal for the resumption of harmonics, the algorithm still applies. However, the procedure did not give a concrete realization.)

说明：  programa de la segunda practica para analisis de se&ntilde ales biomedicas con calculo de ecg

FTF自适应算法 求：自适应滤波器的两个权值ω0 (n)和ω1(n)分别收敛于0.2和0.7的收敛轨迹，并与LMS算法进行对比。(FTF adaptive algorithm Requirements: two weights ω0 is (n) of the adaptive filter and ω1 (n) converges to 0.2 and 0.7, convergence trajectory, and compared with the LMS algorithm.)

产生一个随机信号和两个不同频率但频率间隔很小的正弦信号，要求对两信号之和进行如下分析： （1） 求该随机信号的自相关性系数、自相关函数，画出对应的图形； （2） 利用不同的参数建模方法求出两个随机信号的功率谱； （3） 利用极大似然估计、递推最小二乘法等常用的参数估计方法估计所建模型，包括AR模型、MA模型和ARMA模型的的参数，阶次自定；并与Matlab工具箱里的一些建模函数的运算结果进行比较； （4） 利用陷波滤波和MUSIC滤波方法对该信号的频谱进行估计； （5） 利用Wiener滤波、LMS滤波对该含噪声的正弦信号进行去噪声处理； （6） 假设该信号是一个飞行器的某个方向的线位移信号，可否利用Kalman滤波对该信号进行滤波？ （7） 利用高阶谱理论对该信号进行谱估计和相应的AR模型、MA模型和ARMA模型估计； （8） 利用小波变换（变换函数可以直接用Matlab里的函数）对该信号进行去噪声处理，并和前面的去噪声方法进行比较。 (Produce a random signal and two different frequency but frequency interval small sine signals, required to make the following analysis of two signals: (1) for the random signal from the correlation coefficients, the autocorrelation function and draw the corresponding graphics (2) make use of different parameters modeling method for out two random signal power spectrum (3) using maximum likelihood estimation, recursive least square method and common parameters estimation method estimates that the model, including AR model, MA model and the parameters of the ARMA model we, order time decided oneself With Matlab toolbox and some of the modeling function is used compared the (4) use trapped wave filter and MUSIC of the signal filter method of spectrum to estimate (5) use Wiener filtering, LMS filtering on the sinusoidal signal with noise to noise treatment (6) assumes the signal is a vehicle of a certain direction of displacement signal line, can you use Kalman filtering on the)

Code implementation of a Multilayer Perceptron that learns the logical XOR function (for 2 and 4 inputs).

Multi-User Diversity vs. Accurate Channel State Information in MIMO Downlink Channels Niranjay Ravindran and Nihar Jindal University of Minnesota, Minneapolis, MN 55455

说明：  坐标系Park、Clark变换示例以及逆变换(Park and Clark transformation simulation)

a bunch of useful functions for image reconstruction

code for GMSK scripted in matlab language