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Back Propogation Algorithm

02 Apr 2009

The code implements the Back prop algorithm for MLPs.

File Information
Description	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 :)
MATLAB release	MATLAB 7.0.1 (R14SP1)
Zip File Content
Other Files	BacProp.m, data1in, data1out, initialise.m, plotter.m

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Everyone's Tags	back propogation, learning algorithms, mlp, neural networks(2)
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Comments and Ratings (1)
14 May 2009	keys happ	thank you

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Tag Activity for this File
Tag	Applied By	Date/Time
back propogation	Anshuman Gupta	02 Apr 2009 13:36:23
neural networks	Anshuman Gupta	02 Apr 2009 13:36:23
learning algorithms	Anshuman Gupta	02 Apr 2009 13:36:23
mlp	Anshuman Gupta	02 Apr 2009 13:36:23
neural networks	hemanth kumar	29 Oct 2009 01:20:47

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