Scilab Function
Last update : 13/3/2006

ANN_LMBR - Function to train a feed-forward artificial neural network with one hidden layer.

Calling Sequence

[W,OUT,RMSE,[SSE,GAMK,SSX]] = ANN_LMBR(IN,TARG,Nhid,Wini,[EPOCH,EpochShow,GraphFin,...])

Parameters

Description

The activation function of the hidden layer is the hyperbolic tangent and the identity function for the output layer.

The objective function to be minimized is the Sum of Squared Errors (SSE).

The training algorithm is Levenberg-Marquadt algorithm with bayesian regulation.

Examples

   // Calibration of a network with 6 input nodes, 4 nodes in the hidden layer and 1 output node
   IN   = rand(6,100);
   TARG = rand(1,100);
   Wini = rand(4,7,2);
   [W,OUT,RMSE] = ANN_LMBR(IN,TARG,4,Wini);
  

See Also

ANN_CONV_W ,   ANN_JACOB ,   ANN_NORM ,   ANN_SIM ,  

Authors

Julien Lerat CEMAGREF Antony, HBAN Unit, julien.lerat@cemagref.fr

Bibliography

MacKay, Neural Computation, vol. 4, no. 3, 1992, pp. 415-447. Foresee and Hagan, Proceedings of the International Joint Conference on Neural Networks, June, 1997.

Used Function

ANN_CONV_W, ANN_JACOB