Back Propogation Algorithm

Versión 1.0.0.0 (5,03 KB) por Anshuman Gupta
The code implements the Back prop algorithm for MLPs.
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Actualizado 2 abr 2009

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The training input vectors and target vectors are read from files data1in and data1out respectively. The no of nodes in input and output layer is decided depending on the no. of rows in these datasets.
The no of hidden layers, No of nodes in each hidden layer and the target error (put 0.1) is to be input by the user.

Learning curve is plotted after every 100 epochs.
Learning factor can be varied using the slider at the bottom. This idea was picked from an algorithm created by by AliReza KashaniPour & Phil Brierley.
Activation function for hidden layers is logsig and linear for output layer!
Just press F5 and ve funn!
anshuman0387[at]yahoo[dot]com :)

Citar como

Anshuman Gupta (2024). Back Propogation Algorithm (https://www.mathworks.com/matlabcentral/fileexchange/23528-back-propogation-algorithm), MATLAB Central File Exchange. Recuperado .

Compatibilidad con la versión de MATLAB
Se creó con R14SP1
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Versión Publicado Notas de la versión
1.0.0.0