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baotong
- 报童问题的计算机仿真 ％tm一轮实验的预定模拟天数 ％t一轮实验的仿真天数累积值 ％z订报量 ％z 最优订报量 ％g订报量z之上界 ％s1损失值之累计值 ％s最小损失值值 ％r按概率分布产生随机售报量样本-newsboy problem of computer simulation% tm an experimental simulation of the target number of days a t% of the experimental days of
fit_maxwell_pdf
- fit_maxwell_pdf - Non Linear Least Squares fit of the maxwellian distribution. given the samples of the histogram of the samples, finds the distribution parameter that fits the histogram samples. fits data to the probability of the form:
fit_ML_laplace
- fit_ML_normal - Maximum Likelihood fit of the laplace distribution of i.i.d. samples!. Given the samples of a laplace distribution, the PDF parameter is found fits data to the probability of the form: p(x) = 1/(2*b)*exp(-abs(x-u)/b)
fit_ML_log_normal
- fit_ML_normal - Maximum Likelihood fit of the laplace distribution of i.i.d. samples!. Given the samples of a laplace distribution, the PDF parameter is found fits data to the probability of the form: p(x) = 1/(2*b)*exp(-abs(x-u)/b)
fit_ML_maxwell
- fit_ML_normal - Maximum Likelihood fit of the log-normal distribution of i.i.d. samples!. Given the samples of a log-normal distribution, the PDF parameter is found fits data to the probability of the form: p(x) = sqrt(1/(2*pi))/(s*x)*
fit_ML_normal
- fit_ML_normal - Maximum Likelihood fit of the normal distribution of i.i.d. samples!. Given the samples of a normal distribution, the PDF parameter is found fits data to the probability of the form: p(r) = sqrt(1/2/pi/sig^2)*exp(-((r-u
fit_ML_rayleigh
- 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 wit
fit_rayleigh_pdf
- fit_rayleigh_pdf - Non Linear Least Squares fit of the Rayleigh distribution. given the samples of the histogram of the samples, finds the distribution parameter that fits the histogram samples.fits data to the probability of the form: p(r)=r*exp(-
Fading-channel-simulation
- 衰落信道仿真 function r = rayleigh( fd, fs, Ns ) r = rayleigh(fd,fs,N) A Rayleigh fading simulator based on Clarke s Model Creates a Rayleigh random process with PSD determined by the vehicle s speed. INPUTS: fd = doppler frequency
Modeling-Rayleigh-fading-channel-based-on-modifie
- This Matlab Code models a Rayleigh fading channel using a modified Jakes channel model. A modified Jakes model chooses slightly different spacings for the scatterers and scales their waveforms using Walsh–Hadamard sequences to ensure zero cross-co
fs_sup_relieff
- Relief算法中特征和类别的相关性是基于特征对近距离样本的区分能力。算法从训练集D中选择一个样本R，然后从和R同类的样本中寻找最近邻样本H，称为Near Hit，从和R不同类的样本中寻找最近样本M，称为Near Miss，根据以下规则更新每个特征的权重： 如果R和Near Hit在某个特征上的距离小于R和Near Miss上的距离，则说明该特征对区分同类和不同类的最近邻是有益的，则增加该特征的权重；反之，如果R和Near Hit在某个特征上的距离大于R和Near Miss上的距离，则说明该特