# crosschannelnorm

## Syntax

## Description

The cross-channel normalization operation uses local responses
in different channels to normalize each activation. Cross-channel normalization typically
follows a `relu`

operation.
Cross-channel normalization is also known as local response normalization.

**Note**

This function applies the cross-channel normalization operation to `dlarray`

data. If
you want to apply cross-channel normalization within a `dlnetwork`

object use `crossChannelNormalizationLayer`

.

normalizes each element of `Y`

= crosschannelnorm(`X`

,`windowSize`

)`X`

with respect to local values in the same
position in nearby channels. The normalized elements in `Y`

are calculated
from the elements in `X`

using the following formula.

$$y=\frac{x}{{\left(K+\frac{\alpha *ss}{windowSize}\right)}^{\beta}}$$

where *y* is an element of `Y`

,
*x* is the corresponding element of `X`

,
*ss* is the sum of the squares of the elements in the channel region
defined by `windowSize`

, and *α*, *β*,
and *K* are hyperparameters in the normalization.

also specifies the dimension format `Y`

= crosschannelnorm(`X`

,`windowSize`

,'DataFormat',FMT)`FMT`

when `X`

is an
unformatted `dlarray`

, in addition to the input arguments the previous
syntax. The output `Y`

is an unformatted dlarray with the same dimension
order as `X`

.

specifies options using one or more name-value pair arguments in addition to the input
arguments in previous syntaxes. For example, `Y`

= crosschannelnorm(___,`Name,Value`

)`'Beta',0.8`

sets the value of
the *β* contrast constant to `0.8`

.

## Examples

## Input Arguments

## Output Arguments

## More About

## Extended Capabilities

## Version History

**Introduced in R2020a**