| Author | Message | ||
     David Cameron (david_cameron) New member Username: david_cameron Post Number: 2 Registered: 3-2011 |
Rather than guessing, ask the vendor. They should document the algoritms for you. Pragmatically, the one which gives the best validation result is probably the best. I prefer the area normalization, if it is gives all spectra an area of 1. If you work through the equations you eliminate the pathlength dependence. Same thing happens in MSC when you break it down. | ||
| May Mah (may) New member Username: may Post Number: 1 Registered: 11-2010 |
Hi everyone, I have a set of spectra from mapping my sample and I would like to normalise it. There are six normalisation methods (ie. area, unit vector, mean, maximum, range and peak normalisation) that are availavle in Unscrambler. How to determine which is the best normalisation method for my data? I understand that the area and mean normalisation methods will normalise the spectra so that all of them have the same area under the curve. I know the calculations that are involved in unit vector, maximum and range normalisation methods. However, I don't really know what they do to the spectra. Does anyone have any references that discuss about the different types of normalisation methods? Thanks, May |