Neural Network Toolbox

dmse

Mean squared error performance derivatives function

Syntax

dPerf_dE = dmse('e',E,X,perf,PP)

dPerf_dX = dmse('x',E,X,perf,PP)

Description

dmse is the derivative function for mse.

dmse('d',E,X,PERF,PP) takes these arguments,

• E - Matrix or cell array of error vector(s).

  X - Vector of all weight and bias values.

  perf - Network performance (ignored).

  PP - Performance parameters (ignored).

and returns the derivative dPerf/dE.

dmse('x',E,X,PERF,PP) returns the derivative dPerf/dX.

Examples

Here we define E and X for a network with one 3-element output and six weight and bias values.

• E = {[1; -2; 0.5]};
  X = [0; 0.2; -2.2; 4.1; 0.1; -0.2];
  

Here we calculate the network's mean squared error performance, and derivatives of performance.

• perf = mse(E)
  dPerf_dE = dmse('e',E,X)
  dPerf_dX = dmse('x',E,X)
  

Note that mse can be called with only one argument and dmse with only three arguments because the other arguments are ignored. The other arguments exist so that mse and dmse conform to standard performance function argument lists.

See Also

mse

dmae

dmsereg