henonowntry2

implementation of windows for filters using matlab code with examples

阵列天线抗干扰 圆阵等高线，波束方向及三位角度信噪图(Array antenna interference contours, angle of beam direction and three noise graph)

This programm is main to deal with a periodic flow in the pipe which is part of it

改进的OFDM 子载波分配、功率分配 注水算法(Improved OFDM subcarrier allocation, power allocation, algorithm water)

the simulink of DF coorpertive communication

narrow-band interference suppression in order to avoid the narrow band communication systems has been caused by interference

擅 蔓：以人脸的表情识别为实验背景， 分析了在对人脸表情的识别过程中，单个独立分薰对识别率的影响，由此进一步总结了在表情识 别中如何更有效地选取独立子空间，以实现在不影响识别率的前提下，减少用于构成独立子空问所需的独立分量的个数。 独立成分分析；表情识别；独立子空间 (Good man: Face to face identification for the experimental background, the analysis of facial expressions in the identification process, a single smoked separate the impact of the recognition rate, thus further summarized in the expression recognition of how to more effectively select the independent sub-space in order to achieve the recognition rate does not affect the premise, for constituting a separate sub-reducing space required for the number of independent component. Independent component analysis expression recognition independent subspace)

对具有随机噪声的二阶系统的模型辨识，进行标幺化以后系统的参考模型差分方程为 (7.90) 式中， 为随机噪声。由于神经网络的输出最大为1，所以，被辨识的系统应先标幺化，这里标幺化系数为5。利用图7.5正向建模(并联辨识)结构，神经网络选用3-9-9-1型，即输入层i，隐层j包括2级，输出层k的节点个数分别为3、9、9、1个； (Model identification of two order systems with stochastic noise)

MATLAB 教程 含源程序(MATLAB Tutorial with source code)

fit_ML_rayleigh - Maximum Likelihood fit of the rayleigh distribution of i.i.d. samples!. Given the samples of a rayleigh distribution, the PDF parameter is found fits data to the probability of the form: p(r)=r*exp(-r^2/(2*s))/s with parameter: s format: result = fit_ML_rayleigh( x,hAx ) input: x - vector, samples with rayleigh distribution to be parameterized hAx - handle of an axis, on which the fitted distribution is plotted if h is given empty, a figure is created. output: result - structure with the fields s - fitted parameter CRB - Cram?r-Rao Bound for the estimator value RMS - RMS error of the estimation type- ML