hardlims

Symmetric hard-limit transfer function

Syntax

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

Description

`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.

Examples

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'; ```

Algorithms

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

Version History

Introduced before R2006a