Neural Network Toolbox

premnmx

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

Syntax

[PN,minp,maxp,TN,mint,maxt] = premnmx(P,T)

[PN,minp,maxp] = premnmx(P)

Description

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);
  

Algorithm

• pn = 2*(p-minp)/(maxp-minp) - 1;
  

See Also

prestd, prepca, postmnmx

poststd

prepca

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