Hard-limit transfer function
A = hardlim(N,FP)
hardlim
is a neural transfer function. Transfer functions calculate a
layer’s output from its net input.
A = hardlim(N,FP)
takes N
and optional function
parameters,
N |
|
FP | Struct of function parameters (ignored) |
and returns A
, the S
-by-Q
Boolean
matrix with 1s where N
≥ 0.
info = hardlim('
returns information
according to the code string specified:code
')
hardlim('name')
returns the name of this function.
hardlim('output',FP)
returns the [min max]
output
range.
hardlim('active',FP)
returns the [min max]
active
input range.
hardlim('fullderiv')
returns 1 or 0, depending on whether
dA_dN
is
S
-by-S
-by-Q
or
S
-by-Q
.
hardlim
('fpnames')
returns the names of the function
parameters.
hardlim('fpdefaults')
returns the default function parameters.
Here is how to create a plot of the hardlim
transfer function.
n = -5:0.1:5; a = hardlim(n); plot(n,a)
Assign this transfer function to layer i
of a network.
net.layers{i}.transferFcn = 'hardlim';
hardlim(n)
= 1 if n
≥ 0
0 otherwise