Scilab Function
Last update : 13/3/2006

ANN_SIM - Function to simulate the outputs of a feed-forward artificial neural network with one hidden layer

Calling Sequence

[OUT,[IN_W,HID_OUT]] = ANN_SIM(IN,Nhid,Nout,W)

Parameters

Description

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

Note : weighted output from the hidden layer is equal to HID_OUT because of the identity activation function

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Examples

   // Ouput from a network with 6 input nodes, 4 nodes in the hidden layer and 1 output node
   IN = rand(6,100);
   W  = rand(4,7,2);
   [OUT,IN_W,HID_OUT] = ANN_SIM(IN,4,1,W)   
  

See Also

ANN_LMBR ,   ANN_NORM ,   ANN_JACOB ,   ANN_CONV_W ,   ANN_JACOB ,  

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

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