Neural Network Toolbox

prestd

Preprocess data so that its mean is 0 and the standard deviation is 1

Syntax

[pn,meanp,stdp,tn,meant,stdt] = prestd(p,t)

[pn,meanp,stdp] = prestd(p)

Description

prestd preprocesses the network training set by normalizing the inputs and targets so that they have means of zero and standard deviations of 1.

prestd(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

  meanp -- R x 1 vector containing mean for each P

  stdp -- R x 1 vector containing standard deviations for each P

  tn -- S x Q matrix of normalized target vectors

  meant -- S x 1 vector containing mean for each T

  stdt -- S x 1 vector containing standard deviations for each T

Examples

Here is the code to normalize a given data set so that the inputs and targets will have means of zero and standard deviations of 1.

• p = [-0.92 0.73 -0.47 0.74 0.29; -0.08 0.86 -0.67 -0.52 0.93];
  t = [-0.08 3.4 -0.82 0.69 3.1];
  [pn,meanp,stdp,tn,meant,stdt] = prestd(p,t);
  

If you just want to normalize the input,

• [pn,meanp,stdp] = prestd(p);
  

Algorithm

• pn = (p-meanp)/stdp;
  

See Also

premnmx, prepca

prepca

purelin

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