# reduce HOG features with PCA

I wrote a program,in which I am targeting for classification of object via neural net.I calculated HOG vector by my own(I didn't used prebuild HOG descriptor).I reduced those feature using PCA...where I obtained three Eigen values and its corresponding Eigen vector.Now how shall I feed those Eigen values to neural net??I mean each Eigen vector is of nine dimension and there are total three...do we need to catenate all together to make a (9x3=27 dimensional vector in a single row) or do something else like resultanting all together??