ma86kbl@cc.brunel.ac.uk (Kam B Lo) (04/10/90)
I am trying to train a three-layered neural network (1 layer of input,
1 hidden layer and 1 output layer) to classify two groups of chemical
compounds by their NIR spectrascopic data using the back-propagation
technique. Each of the NIR spectrum consists of 700 values in the range
of -0.03 to 0.03.
My problem is what preprocessing do I need to do to this data to get it
in an acceptable form for entering into the neural network. I have tried
setting up a network with 700 input cells and assigning them to the
corresponding values on the spectrum (is this sensible?), but this
always got stuck in a local minimum.
Any help with this problem will be greatly appreciated,
Kam.