Neural Network Toolbox™

Competitive transfer function

Graph and Symbol

Syntax

• A = compet(N,FP)
  dA_dN = compet('dn',N,A,FP)
  info = compet(code)
  

Description

compet is a neural transfer function. Transfer functions calculate a layer's output from its net input.

compet(N,FP) takes N and optional function parameters,

N	S x Q matrix of net input (column) vectors
FP	Struct of function parameters (ignored)

and returns the S x Q matrix A with a 1 in each column where the same column of N has its maximum value, and 0 elsewhere.

compet('dn',N,A,FP) returns the derivative of A with respect to N. If A or FP is not supplied or is set to [], FP reverts to the default parameters, and A is calculated from N.

compet('name') returns the name of this function.

compet('output',FP) returns the [min max] output range.

compet('active',FP) returns the [min max] active input range.

compet('fullderiv') returns 1 or 0, depending on whether dA_dN is S x S x Q or S x Q.

compet('fpnames') returns the names of the function parameters.

compet('fpdefaults') returns the default function parameters.

Examples

Here you define a net input vector N, calculate the output, and plot both with bar graphs.

• n = [0; 1; -0.5; 0.5];
  a = compet(n);
  subplot(2,1,1), bar(n), ylabel('n')
  subplot(2,1,2), bar(a), ylabel('a')
  

Assign this transfer function to layer i of a network.

• net.layers{i}.transferFcn = 'compet';
  

See Also

sim, softmax

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