j02_merrysims

PolInSAR滤波，采用IDAN（基于强度的自适应邻域）算法，matlab程序(PolInSAR filtering, using IDAN (based on strength of the adaptive neighborhood) algorithm, matlab program)

巴特沃斯高通滤波matlab编程，很实用，(Butterworth high-pass filter Matlab programming, very useful, thank you)

matlab是一门简单易学的重要工具，一个简明的例程可以事半功倍。(matlab is an easy to learn an important tool for a concise routines can do more with less.)

eBook on Matlab for Science Engineers.

Standard dispersion for fiber opticsvformula from Corning

说明：  大气层内航天器飞行动力学matlab仿真模型(The atmosphere inside the spacecraft flight dynamics matlab simulation model)

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)

可直接运行的基于拉普拉斯以及小波变换的多种融合方法的代码(Can be run directly based on the Laplace and the wavelet transform multiple fusion method code)

各种加权函数后互相关功率谱的计算，比较，可用于定位系统的时延估计(After various weighting function cross-correlation power spectrum calculation, comparison, can be used for positioning system (GPS) time delay estimation)

本代码讲了在matlab中实现数据的预处理的方法（包括标准化变化）等(The M codes describe how to pre-treat the datas in matlab (including the standardized convertion) etc.)