代码搜索：Variance

找到约 2,271 项符合「Variance」的源代码

代码结果 2,271
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m rbf_kernel.m

function x = RBF_kernel(a,b, sigma2) % Radial Basis Function (RBF) kernel function for implicit higher dimension mapping % % X = RBF_kernel(a,b,sig2) % % 'sig2' contains the SQUARED variance of the R
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www.eeworm.com/read/412611/11190667

m noisecg.m

function noise=noisecg(N,a1,a2) %NOISECG Analytic complex gaussian noise. % NOISE=NOISECG(N,A1,A2) computes an analytic complex gaussian % noise of length N with mean 0.0 and variance 1.0. % % NOISE=
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www.eeworm.com/read/335058/12552120

m noisecg.m

function noise=noisecg(N,a1,a2) %NOISECG Analytic complex gaussian noise. % NOISE=NOISECG(N,A1,A2) computes an analytic complex gaussian % noise of length N with mean 0.0 and variance 1.0. % % NOISE=
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www.eeworm.com/read/146860/12607007

m noisecg.m

function noise=noisecg(N,a1,a2) %NOISECG Analytic complex gaussian noise. % NOISE=NOISECG(N,A1,A2) computes an analytic complex gaussian % noise of length N with mean 0.0 and variance 1.0. % % NOISE=
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www.eeworm.com/read/237026/13980830

m noisecg.m

function noise=noisecg(N,a1,a2) %NOISECG Analytic complex gaussian noise. % NOISE=NOISECG(N,A1,A2) computes an analytic complex gaussian % noise of length N with mean 0.0 and variance 1.0. % % NOISE=
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www.eeworm.com/read/133638/14032697

m noisecg.m

function noise=noisecg(N,a1,a2) %NOISECG Analytic complex gaussian noise. % NOISE=NOISECG(N,A1,A2) computes an analytic complex gaussian % noise of length N with mean 0.0 and variance 1.0. % % NOISE=
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www.eeworm.com/read/132819/14071966

m noisecg.m

function noise=noisecg(N,a1,a2) %NOISECG Analytic complex gaussian noise. % NOISE=NOISECG(N,A1,A2) computes an analytic complex gaussian % noise of length N with mean 0.0 and variance 1.0. % % NOISE=
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www.eeworm.com/read/201218/15413206

m rbf_kernel.m

function x = RBF_kernel(a,b, sigma2) % Radial Basis Function (RBF) kernel function for implicit higher dimension mapping % % X = RBF_kernel(a,b,sig2) % % 'sig2' contains the SQUARED variance of the R
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www.eeworm.com/read/184950/9064002

m bayesmean.m

function y = bayesmean(mu, sigma, mu0, sigma0, N, x) % y = bayesmean(mu, sigma, mu0, sigma0, N, x) % % Bayesian learning of the mean of a Gaussian with known variance. % N samples are drawn
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www.eeworm.com/read/419826/10834846

m channel.m

function y = channel(sig2, Mt, Mr, x, H, N); % function y = channel(sig2, Mt, Mr, x, H, N) % % Channel transmission simulator % % inputs: % sig2 - noise variance % Mt - number of Tx antenna
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