I'm working on a neural network with back propagation for indoor localization. The input of the neural network is Received Signal Strengths (RSSs) and the output is a coordinate (x,y). I have normalized the input and output for training.
I used this equation for normalization:
normalized value = minOfNormalizedScale+(old value- minOfPreviousScale)(maxOfNewScale- minOfNormalizedScale)/(maxOfPreviousScale – minOfPreviousScale).
the new space is [0,1] the old space depends of the recorded values of RSSs , x , and y.
For localization process I need the error of the neural network to be measure in meters. How can I de-normalize the result of the neural network( the coordinates)?.
I tried using this equation:
old value= normalized value*(maxOfOldScale-minOfOldScale)+minOfOldScale +.
is it correct?