代码搜索：Hyper
找到约 912 项符合「Hyper」的源代码
代码结果 912
www.eeworm.com/read/374698/9388816
m bay_optimize.m
function [model,A,B,C,D] = bay_optimize(model,level, type, nb, bay)
% Optimize the posterior probabilities of model (hyper-) parameters with respect to the different levels in Bayesian inference
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www.eeworm.com/read/278889/10490437
m bay_optimize.m
function [model,A,B,C,D] = bay_optimize(model,level, type, nb, bay)
% Optimize the posterior probabilities of model (hyper-) parameters with respect to the different levels in Bayesian inference
%
%
www.eeworm.com/read/421949/10676027
m bay_optimize.m
function [model,A,B,C,D] = bay_optimize(model,level, type, nb, bay)
% Optimize the posterior probabilities of model (hyper-) parameters with respect to the different levels in Bayesian inference
%
%
www.eeworm.com/read/469123/6977817
m approxla.m
function [alpha, sW, L, nlZ, dnlZ] = approxLA(hyper, covfunc, lik, x, y)
% Laplace approximation to the posterior Gaussian Process.
% The function takes a specified covariance function (see covFuncti
www.eeworm.com/read/397122/8065750
m bay_optimize.m
function [model,A,B,C,D] = bay_optimize(model,level, type, nb, bay)
% Optimize the posterior probabilities of model (hyper-) parameters with respect to the different levels in Bayesian inference
%
%
www.eeworm.com/read/331336/12832399
m bay_optimize.m
function [model,A,B,C,D] = bay_optimize(model,level, type, nb, bay)
% Optimize the posterior probabilities of model (hyper-) parameters with respect to the different levels in Bayesian inference
%
%
www.eeworm.com/read/142329/12951800
asm motor_com1.asm
;This routine dispalys few key parameters on Hyper terminal.
;Baud rate set to 9600
;Parameters displayed can be changed in the main motor control program
;After debugging, this program can be rem
www.eeworm.com/read/324303/13273663
m bay_optimize.m
function [model,A,B,C,D] = bay_optimize(model,level, type, nb, bay)
% Optimize the posterior probabilities of model (hyper-) parameters with respect to the different levels in Bayesian inference
%
%
www.eeworm.com/read/318947/13465958
m bay_optimize.m
function [model,A,B,C,D] = bay_optimize(model,level, type, nb, bay)
% Optimize the posterior probabilities of model (hyper-) parameters with respect to the different levels in Bayesian inference
%
%
www.eeworm.com/read/316944/13513992
m bay_optimize.m
function [model,A,B,C,D] = bay_optimize(model,level, type, nb, bay)
% Optimize the posterior probabilities of model (hyper-) parameters with respect to the different levels in Bayesian inference
%
%