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