premnmx (Neural Network Toolbox)

Preprocess data so that minimum is -1 and maximum is 1

[pn,minp,maxp,tn,mint,maxt] = premnmx(p,t)

[pn,minp,maxp] = premnmx(p)

premnmx preprocesses the network training set by normalizing the inputs and targets so that they fall in the interval [-1,1].

premnmx(P,T) takes these inputs,

P - R x Q matrix of input (column) vectors.

T - S x Q matrix of target vectors.

and returns,

PN - R x Q matrix of normalized input vectors.

minp- R x 1 vector containing minimums for each P.

maxp- R x 1 vector containing maximums for each P.

TN - S x Q matrix of normalized target vectors.

mint- S x 1 vector containing minimums for each T.

maxt- S x 1 vector containing maximums for each T.

Examples

Here is the code to normalize a given data set so that the inputs and targets will fall in the range [-1,1].

p = [-10 -7.5 -5 -2.5 0 2.5 5 7.5 10];
t = [0 7.07 -10 -7.07 0 7.07 10 7.07 0];
[pn,minp,maxp,tn,mint,maxt] = premnmx(p,t);

If you just want to normalize the input,

[pn,minp,maxp] = premnmx(p);

pn = 2*(p-minp)/(maxp-minp) - 1;