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Thread Subject:
neural network input

Subject: neural network input

From: srishti

Date: 20 Feb, 2013 17:24:10

Message: 1 of 2

hi everyone,
   I am using Empirical mode decomposition, for feature extraction of an image, I will take first three IMFs, then suppose I want to take statistical features like mean, standard deviation,energy . So can anybody suggest me how to prepare that data for neural network classifier input ?

Subject: neural network input

From: Greg Heath

Date: 22 Feb, 2013 01:44:09

Message: 2 of 2

"srishti " <srishti.sondele@gmail.com> wrote in message <kg30rq$5i3$1@newscl01ah.mathworks.com>...
> hi everyone,
> I am using Empirical mode decomposition, for feature extraction of an image, I will take first three IMFs, then suppose I want to take statistical features like mean, standard deviation,energy . So can anybody suggest me how to prepare that data for neural network classifier input ?

If you have N samples of I features, the size of the input matrix is

[ I N ] = size(input)

The size of the corresponding target matrix for c classes is

[ c N ] = size(target)

The target columns are columns of the c-dimensional unit matrix eye(c) with the row index of the 1 indicating the class index of the corresponding input vector.

See the classification/pattern-recognition demos using patternnet.

help/doc patternnet
help/doc nndatasets

Hope this helps.

Greg

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