quadraticLayer
Quadratic layer
Description
A quadratic layer calculates the pair-wise products of the elements of the input (the quadratic monomials).
Creation
Description
Input Arguments
Properties
This property is read-only.
One-line description of the layer, stored as 'Quadratic'
. This
description appears when you display a Layer
array and when you use the
analyzeNetwork
function.
This property is read-only.
Type of the layer, stored as 'Quadratic'
. The type appears when
you display a Layer
array and when you use the analyzeNetwork
function.
This property is read-only.
Number of inputs to the layer, stored as 1
. This layer accepts a
single input only.
Data Types: double
This property is read-only.
Input names, stored as {'in'}
. This layer accepts a single input
only.
Data Types: cell
This property is read-only.
Number of outputs from the layer, stored as 1
. This layer has a
single output only.
Data Types: double
This property is read-only.
Output names, stored as {'out'}
. This layer has a single output
only.
Data Types: cell
Examples
Create a quadratic layer with the name "quad"
.
layer = quadraticLayer(Name="quad")
layer = QuadraticLayer with properties: Name: 'quad' Learnable Parameters No properties. State Parameters No properties. Show all properties
Include a quadratic layer in a layer array.
layers = [ featureInputLayer(3) quadraticLayer fullyConnectedLayer(1)];
Algorithms
A quadratic layer calculates the pair-wise products of the elements of the input (the quadratic monomials).
The output of the layer is
where
is the layer input.
Layers in a layer array or layer graph pass data to subsequent layers as formatted dlarray
objects.
The format of a dlarray
object is a string of characters in which each
character describes the corresponding dimension of the data. The format consists of one or
more of these characters:
"S"
— Spatial"C"
— Channel"B"
— Batch"T"
— Time"U"
— Unspecified
For example, you can describe 2-D image data that is represented as a 4-D array, where the
first two dimensions correspond to the spatial dimensions of the images, the third
dimension corresponds to the channels of the images, and the fourth dimension
corresponds to the batch dimension, as having the format "SSCB"
(spatial, spatial, channel, batch).
QuadraticLayer
objects support data of any format with one or two
dimensions only. The layer operates over the first dimension. The layer and does not add or
remove any dimensions and outputs data with the same format the input data.
Version History
Introduced in R2019aThis layer now requires Deep Learning Toolbox™ only. In previous releases, this layer also required Reinforcement Learning Toolbox™.
There are some changes to the layer:
The default value of the
Description
property is'Quadratic'
. In previous releases, the default value is'Quadratic layer'
.Setting the
Description
using a name-value argument is not recommended. Use the default value instead. Code that sets theDescription
argument continues to work.The default value of the
Type
property is'Quadratic'
. In previous releases, the default value is"QuadraticLayer"
.quadraticLayer
objects have different class names. If you have code that refers to the previous class names of these objects, then replace the references with the new class names. In most cases, your code will continue to run.This table shows the change of outputs of the
class
function for this layers.layer
class(layer)
(Before R2025a)class(layer)
(Starting in R2025a)quadraticLayer
object'rl.layer.QuadraticLayer'
'nnet.cnn.layer.QuadraticLayer
The
isa
function returns the same value as for previous releases. For example, in R2025a, bothisa(layer,"nnet.cnn.layer.QuadraticLayer")
andisa(layer,"rl.layer.QuadraticLayer")
return1
(true
) forquadraticLayer
objects.If you have code that uses the value returned by the
class
function, then you must update your code to use the new class name. For example, replace instances ofwithif class(layer) == "rl.layer.QuadraticLayer" ... end
if isa(layer,"nnet.cnn.layer.QuadraticLayer") ... end
See Also
dlnetwork
| trainingOptions
| trainnet
| scalingLayer
| softplusLayer
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