elm

matlab code from the states university of new york in the united states

这是一个matlab控制倒立摆的文件，其利用了模糊控制的方法。(This is a matlab inverted pendulum control of the paper, their use of fuzzy control method.)

仿真实现了MUSIC、Beamformer、Capon功率谱，并未实现线性预测功率谱估计（未找到方法）。由实验结果我们可以得出结论MUSIC的估计效果最好，它可以区分800、850处来波，其他角度也可区分。(Simulation of MUSIC, Beamformer, Capon power spectrum, did not realize the power spectrum estimation linear prediction (not way to find). From the experimental results, we can draw the conclusion MUSIC best estimate of the effect, it can be distinguished to wave at 800, 850, other angles can also be distinguished.)

MATLAB二维绘图，通过TXT文件读取数据(MATLAB 2D plot read data TXT)

This code generate LFM chirp with any length, cycles, delays, and phase offsets. It also ensure continous phase change from one pulse to the other.

一种实现matlab和c#结合的小例子，有待进一步改进(An implementation matlab and c# combination small example, be further improved)

遗传算法相关文档，对遗传算法的讲解清晰明了。(Genetic algorithms related documents, genetic algorithm on clarity.)

这是Harris角点算法的一个非常好的参考代码，使用的是Matlab语言，实现了非最大抑制功能。(The code calculates the Harris Feature Points. )

《雷达成像技术》，刘永坦院士的书，就不用多介绍了(" Radar Imaging" , Academician Liu Tan book, do not need to introduce more of the)

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)