velm_train.m

基于BP模型的神经网络模型

function f=velm_train(network,data)
Y = data.target';
% calculate hidden layer output matrix
for i=1:length(Y)
    for j=1:network.regressors
       X(i,j) = tanh( network.w(j,:) * data.vtraining(:,i) + network.b(j) );
    end    
    X(i,network.regressors+1) = 1;
end    
% Batch mode
network.weights = inv(X'*X)*X'*Y;
f = network;
% // include recursiveLeastSquares.m