代码搜索：coefficient

找到约 3,200 项符合「coefficient」的源代码

代码结果 3,200
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m rls2.m

%RLS2 Problem 1.1.1.1.2.3 % % 'ifile.mat' - input file containing: % I - members of ensemble % K - iterations % sigmax - standard deviation of input % Wo - coefficient ve
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www.eeworm.com/read/302326/13837644

m crbf.m

%CRBF Complex Radial Basis Function algorithm % % 'ifile.mat' - input file containing: % Nr - members of ensemble % dim - iterations % Nneur - number of neurons % Sx - standard
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m qrrls2.m

%QRRLS2 Problem 1.1.1.2.8 % % 'ifile.mat' - input file containing: % I - members of ensemble % K - iterations % a1 - coefficient of input AR process % sigmax - standard d
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m lms4.m

%LMS4 Problem 1.1.2.1 % % 'ifile.mat' - input file containing: % I - members of ensemble % K - iterations % sigmax - standard deviation of input % lambdaW, sigmaW - param
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www.eeworm.com/read/302326/13837652

m lms3.m

%LMS3 Problem 1.1.1.2.1 % % 'ifile.mat' - input file containing: % I - members of ensemble % K - iterations % a1 - coefficient of input AR process % sigmax - standard dev
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m rls3.m

%RLS3 Problem 1.1.1.2.3 % % 'ifile.mat' - input file containing: % I - members of ensemble % K - iterations % a1 - coefficient of input AR process % sigmax - standard dev
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www.eeworm.com/read/302326/13837660

m vrls.m

%VRLS Volterra RLS algorithm % % 'ifile.mat' - input file containing: % Nr - members of ensemble % dim - iterations % Sx - standard deviation of input % Sn - standard deviation
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m rls1.m

%RLS1 Problem 1.1.1.1.1.2 % % 'ifile.mat' - input file containing: % I - members of ensemble % K - iterations % sigmax - standard deviation of input % Wo - coefficient ve
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www.eeworm.com/read/302326/13837669

m rls4.m

%RLS4 Problem 1.1.2.2 % % 'ifile.mat' - input file containing: % I - members of ensemble % K - iterations % sigmax - standard deviation of input % lambdaW, sigmaW - param
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www.eeworm.com/read/302326/13837670

m rbf.m

%RBF Radial Basis Function algorithm % % 'ifile.mat' - input file containing: % Nr - members of ensemble % dim - iterations % Nneur - number of neurons % Sx - standard deviation
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