代码搜索:Generates

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www.eeworm.com/read/321160/13411469

m bdt_f527.m

% MATLAB script that generates the probability of error versus the signal to noise ratio initial_snr=0; final_snr=15; snr_step=1; tolerance=1e-7; % Tolerance used for the integration minus_in
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m bdt_f527.m

% MATLAB script that generates the probability of error versus the signal-to-noise ratio initial_snr=0; final_snr=15; snr_step=1; tolerance=1e-7; % tolerance used for the integration min
www.eeworm.com/read/320711/13419711

m sacubic.m

function [ab,vE,E] = sacubic(N); % % Ph.D. Thesis % Leandro Nunes de Castro % October, 1999. % Function generates n-bit binary strings antibody most uniformly % distributed over the search spac
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m donuts.m

function S = donuts; % % Ph.D. Thesis % Leandro Nunes de Castro % February, 2000 % Function generates the dataset for the 2-DONUTS problem % % DONUT 1 step = 0.2; t = 0:step:4*pi; l = le
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m saml.m

function [ab,vE,E] = saml(N); % % Ph.D. Thesis % Leandro Nunes de Castro % October, 1999. % Function generates n-bit binary strings antibody most uniformly % distributed over the search space
www.eeworm.com/read/319604/13448340

m sacubic.m

function [ab,vE,E] = sacubic(N); % % Ph.D. Thesis % Leandro Nunes de Castro % October, 1999. % Function generates n-bit binary strings antibody most uniformly % distributed over the search spac
www.eeworm.com/read/319604/13448343

m donuts.m

function S = donuts; % % Ph.D. Thesis % Leandro Nunes de Castro % February, 2000 % Function generates the dataset for the 2-DONUTS problem % % DONUT 1 step = 0.2; t = 0:step:4*pi; l = le
www.eeworm.com/read/319604/13448367

m saml.m

function [ab,vE,E] = saml(N); % % Ph.D. Thesis % Leandro Nunes de Castro % October, 1999. % Function generates n-bit binary strings antibody most uniformly % distributed over the search space
www.eeworm.com/read/318285/13482108

txt readme.txt

http://web.mit.edu/brzezin/www/359/matlab/ MIMO OFDM Simulator: OFDM.m: OFDM Simulator (outer function) create_channel.m: Generates a Rayleigh fading frequency-selective channel, paramet
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m mmse_mse_calc.m

%Function Declaration: function ms_error=MMSE_MSE_calc(X,H,Y,Rgg,variance); %This function generates mean squared error for the the MMSE estimator.. %EVALUATION OF Hmmse %Hmmse=F*Rgg*inv(Rgy)*Y;