predictions by a neural network with 1 hidden layer and with bias
[ypred]=nns_simul(wh,wo,x)
coefficients of the hidden neurons + bias
wh is a matrix of dimensions ((q+1) x nh) or a Div structure
nh is the number of hidden neurons
coefficients of the output neurons de sortie + bias
wo is a matrix of dimensions ((nh+1) x no) or a Div structure
no is the number of output neurons
calibration dataset
x is a matrix of dimensions (n x q) or a Div structure
predictions obtained from the neural network (wh,wo) applied to x
ypred is a Div structure
ypred.d is a matrix of dimensions (n x no)