hardlims

Symmetric hard-limit transfer function

Graph and Symbol

Symmetric hard-limit transfer function. The function returns -1 if input n is less than or equal to 0, and 1 if n is greater than or equal to 0.

A = hardlims(N,FP)

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

A = hardlims(N,FP) takes N and optional function parameters,

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

and returns A, the S-by-Q +1/–1 matrix with +1s where N ≥ 0.

info = hardlims('code') returns information according to the code string specified:

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

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

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

hardlims('fullderiv') returns 1 or 0, depending on whether dA_dN is S-by-S-by-Q or S-by-Q.

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

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

Here is how to create a plot of the hardlims transfer function.

n = -5:0.1:5;
a = hardlims(n);
plot(n,a)

Assign this transfer function to layer i of a network.

net.layers{i}.transferFcn = 'hardlims';

hardlims(n) = 1 if n ≥ 0, –1 otherwise.

Introduced before R2006a