hardlim

Hard-limit transfer function

Syntax

```A = hardlim(N,FP) ```

Description

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

and returns `A`, the `S`-by-`Q` Boolean matrix with 1s where `N` ≥ 0.

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

`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.

Examples

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'; ```

Algorithms

`hardlim(n)` = 1 if `n` ≥ 0

0 otherwise