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这是自适应均衡器的Matlab仿真实现的代码，能实现自适应均衡器的功能(matlab code)

基于矩阵笔方法的稀疏阵列综合，是一篇引用率很好的文章(matrix pencil)

使用低通滤波器从含有噪声的信号中提取有用的正弦波 (见实验指导书 实验九 数字滤波器中的第一题) 目的：用数字滤波器从含有高频噪声的采样数据中提取正弦信号。 要求：①输入信号为一正弦波，并加入一个白噪声的干扰来模拟信号传输中的随机干扰信号（用以模拟含有噪声采样序列）。 （模拟含有噪声采样序列具体可用正弦波信号叠加高频噪声来实现，为了使滤波效果明显，本实验的高频噪声是用高频均匀分布白噪声（Uniform）通过Butterworth高通滤波器过滤生成的，高通滤波器的截止频率设为10倍输入信号频率。） ②在程序中设计一个低通巴特沃斯滤波器，以滤除信号中的噪声分量，提取输入的正弦波信号 。 ③可调节信号滤波器的截止频率和阶数，可显示滤波前与滤波后的时域信号。 ④给出滤波前与滤波后的频谱特性的显示。 (Using low pass filter extracting useful sine wave signal containing noise(see experiment instruction digital filter in the first nine questions)Objective: to use digital filter sampling data extract containing high frequency noise sine signal.Requirements: (1) the input signal is a sine wave, and add a white noise interference to simulate the random disturbance signal of the signal transmission (to simulate contains noise sampling sequence).(simulated the sampling sequence contains noise available sine wave signal superposition of high frequency noise, in order to make the filtering effect is obvious, the experiment of high frequency noise is Uniform distribution with high frequency white noise (Uniform) by Butterworth high-pass filter to filter generated, high-pass filter cutoff frequency set to 10 times the size of the input signal frequency.)(2) in the program design a low-pass butterworth filter, in order to filter out the noise in the signal component, extract the input sine wav)

LNMF- local non-negative matrix factorization, for face recognition.

Hotkey traping all Keys grom applications

基于最小二乘支持向量机的模式识别，特征向量为滚动轴承的能量百分比和峭度系数(Pattern recognition based on least squares support vector machine (SVM), the percentage of energy eigenvector for rolling bearing and kurtosis coefficient)

数值分析中经典的arnoldi算法，用来求解大型矩阵方程组的求解(numerical analysis classic arnoldi algorithm used to solve large matrix equations Solution)

本程序实现了差分相移键控(DPSK)的调制与解调，得到了眼图。(This program simulates the Differential Phase Shift Keying(DPSK)system to obtain a eye diagram.)

为支持向量机代码，源代码为matlab实现，可以做聚类问题(To support vector machine codes)