how can normalize the data between 0 and 1??

Answers (2)

mat2gray() would normalize to exactly 0 to exactly 1.
But what value do you want instead of 0? Should the smallest values be mapped to eps(realmin), which is about 1E-324 ?

3 Comments

the value should be more then zero but not exactly 0 and less than one. it may take any value as you said eps(realmin) also fine
@ananthi: Accepting an answer means, that the problem is solved. Then most readers will not care about the thread anymore. Is the problem solved?
mat2gray(DATA) * (1-eps) + eps(realmin)

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Jan
Jan on 23 Feb 2017
Edited: Jan on 23 Feb 2017
A cheap adjustment of the edges:
x = randn(100, 1);
xn = (x - min(x)) / (max(x) - min(x));
xn(xn == 0) = eps; % Or: eps(realmin)
xn(xn == 1) = 1 - eps;
Or consider the limits during the normalization: [EDITED, first version failed]
xmin = min(x);
xmax = max(x);
range = (xmax - xmin) + eps(xmax - xmin);
xn = (x - (xmin - eps(xmin))) / range;
% Or:
% xn = (x - (xmin - eps(xmax - xmin))) / range;

4 Comments

thank you jan simon.. this logic is working
Hi can I ask what is the function of eps(xmax-xmin)
sir,what is this x?
It's the data that you want to rescale.

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Asked:

on 23 Feb 2017

Commented:

on 20 Oct 2019

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