代码搜索：Learning

找到约 5,352 项符合「Learning」的源代码

代码结果 5,352
热门代码： main.c GPIO I2C SPI UART timer interrupt ADC PWM LED
www.eeworm.com/read/397106/8067875

m clusmse.m

% ---------------------------------------------------------------- % FUNCTION clusmse.m CLUSterin algorithm, MSE metric. % ---------------------------------------------------------------- % b
·
www.eeworm.com/read/143498/12870428

m adjeta.m

function new_eta = adjeta(eta, rmse) % ADJETA Adjust learning rate eta in SD according to history of RMSE. new_eta = eta;
·
www.eeworm.com/read/328885/12996702

plg ht1621.plg

礦ision3 Build Log Project: E:\learning data\program code\HT1621 driver\HT1621 C-ok\HT1621.uv2 Project File Date: 08/26/2006 Output:
·
www.eeworm.com/read/137160/13342368

m prex_cleval.m

%PREX_CLEVAL PRTools example on learning curves % % Presents the learning curves for Highleyman's classes % help prex_cleval echo on % Set desired learning sizes learnsize = [3 5
·
www.eeworm.com/read/314653/13562570

m prex_cleval.m

%PREX_CLEVAL PRTools example on learning curves % % Presents the learning curves for Highleyman's classes % help prex_cleval echo on % Set desired learning sizes learnsize = [3 5
·
www.eeworm.com/read/493294/6400337

m prex_cleval.m

%PREX_CLEVAL PRTools example on learning curves % % Presents the learning curves for Highleyman's classes % help prex_cleval echo on % Set desired learning sizes learnsize = [3 5
·
www.eeworm.com/read/492695/6419415

m example22a.m

%perc2a %%=============== %%=============== % figure('name','训练过程图示','numbertitle','off'); P=[-0.5 -0.5 0.3 0;-0.5 0.5 -0.5 1]; T=[1 1 0 0]; %initialization [R,Q]=size(P); [S,Q]=size(T)
·
www.eeworm.com/read/492695/6419445

m example22.m

%perc2 %%=============== %%=============== % figure('name','训练过程图示','numbertitle','off'); P=[-0.5 -0.5 0.3 0;-0.5 0.5 -0.5 1]; T=[1 1 0 0]; %initialization [R,Q]=size(P); [S,Q]=size(T);
·
www.eeworm.com/read/492695/6419487

m example24a.m

%perc4 %%=============== %%=============== figure('name','训练过程图示','numbertitle','off'); P=[-0.5 -0.5 0.3 0 -0.8;-0.5 0.5 -0.5 1 0]; T=[1 1 0 0 0]; %initialization [R,Q]=size(P); [S,Q]=size(T
·
www.eeworm.com/read/492695/6419564

m selforganize.m

function [w,wbias,y,d,b,sse]=selforganize(x,c,t) % RBF网络的实现 %x为np×ni的输入矩阵。np为输入样本个数,ni为RBF网络输入层单元数 %c为ni×m的初始中心矩阵。m为中心的个数 %t为np×no的期望输出矩阵。No为RBF网络输出层节单元数 [np,ni]=size(x); d=learning_c(x,c); %学
·