# hardlim

Hard-limit transfer function

## Syntax

``A = hardlim(N)``
``info = hardlim('code')``

## Description

example

````A = hardlim(N)` takes an `S`-by-`Q` matrix of net input (column) vectors, `N`, and returns `A`, the `S`-by-`Q` Boolean matrix with elements equal to `1` where the corresponding elements in `N` are greater than or equal to `0`.`hardlim` is a neural transfer function. Transfer functions calculate a layer’s output from its net input. ```
````info = hardlim('code')` returns useful information for each `code` character vector: `hardlim('name')` returns the name of this function.`hardlim('output')` returns the `[min max]` output range.`hardlim('active')` 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

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This example shows how to create a plot of the `hardlim` transfer function.

Create the input matrix, n. Then call the `hardlim` function and plot the results.

```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'; ```

## Input Arguments

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Net input column vectors, specified as an `S`-by-`Q` matrix.

## Output Arguments

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Output matrix, returned as an `S`-by-`Q` Boolean matrix with elements equal to `1` where the corresponding elements in `N` are greater than or equal to `0`.

## Algorithms

`hardlim(n)` = 1 if `n` ≥ 0

0 otherwise

## Version History

Introduced before R2006a