BLDCM_control

more tools to filter ecgs MIT-BIH arrhthymias.

可将数据平均化，将样本中的异常样本剔除掉，剔除异常样本后进行数据平均(The data can be averaged, the samples of the abnormal sample removed, remove the abnormal sample after the data average)

本代码使用高斯绝对稀疏信号进行重构，采用的重构算法是SAMP，重构效果好！(This code uses the absolute sparse Gaussian signal reconstruction, reconstruction algorithm uses a SAMP, good remodeling effect!)

说明：  广义预测控制仿真的源代码将在这里展示，用MATLAB进行仿真。(a good simulation is shown.)

模式分类的分类器参数设置代码以及其他参数的设计(Pattern classification in the code parameter settings and other parameters of the design)

内点法对非凸非线性规划的解法，求得最优化的解。(Interior point method for solution of non-convex nonlinear programming, to achieve optimum solution.)

这是mimo ofdm系统的仿真程序，代循环前缀，加性高斯噪声，双发双收的系统，(Channel estimation for a MIMO-OFDM system estimation technique subcarriers)

利用SCPI语言，实现基于Matlab的信号发生器控制(With SCPI programming language, implement the control of wareform generator based on Maltab)

code C++ for convulotion coding

2. 设 是窄带信号，定义 是在 区间上均匀分布的随机相位。 是寬带信号，它是一个零均值、方差为1的白噪音信号e(n)激励一个线性滤波器而产生，其差分方程为 。 1） 计算 和 各自的自相关函数，并画出其函数图形。根据此选择合适的延时，以实现谱线增强。 2） 产生一个 序列。选择合适的 值。让 通过谱线增强器。画出输出信号 和误差信号e(n)的波形，并分别与 和 比较。 (Computer Experiments: 1. Consider an AR process x(n) defined by the difference equation where v(n) is an additive white noise of zero mean and variance .The AR parameters and are both real valued: a) Calculate the noise variance such that the AR process x(n) has unit variance .Hence , generate different realization of the process x (n). b) Given the input x (n), an LMS filter of length M = 2 is used to estimate the unknown AR parameters and . The step size is assigned the value 0.05. Compute and plot the ensemble average curve of and by averaging the value of parameters and over an ensemble of 100 different realization of the filter. Calculate the time constant according to the experiment results and compare with the corresponded theoretical value. c) For one realization of the LMS filter, compute the prediction error And the two tap-weight errors and Using power spectral plots of , show that)