convn
N-D convolution
Description
Examples
3-D Convolution
You can control the size of the output of the convn
function. For example, the 'same'
option trims the outer part of the convolution and returns only the central part, which is the same size as the input.
Convolve a random 2-by-3-by-2 array A
with a 2-by-2-by-2 kernel B
. The result is a 3-by-4-by-3 array, which is size(A) + size(B) - 1
.
A = rand(2,3,2); B = 0.25*ones(2,2,2); C = convn(A,B)
C = C(:,:,1) = 0.2037 0.2354 0.1898 0.1581 0.4301 0.6902 0.4426 0.1825 0.2264 0.4548 0.2527 0.0244 C(:,:,2) = 0.2733 0.5444 0.4686 0.1975 0.6365 1.3772 1.2052 0.4645 0.3632 0.8327 0.7366 0.2670 C(:,:,3) = 0.0696 0.3090 0.2788 0.0394 0.2063 0.6869 0.7627 0.2821 0.1367 0.3779 0.4839 0.2426
sizeC = size(A) + size(B) - 1
sizeC = 1×3
3 4 3
Return the central part of the convolution, which is the same size as A
.
C = convn(A,B,'same')
C = C(:,:,1) = 1.3772 1.2052 0.4645 0.8327 0.7366 0.2670 C(:,:,2) = 0.6869 0.7627 0.2821 0.3779 0.4839 0.2426
Input Arguments
A
— Input array
vector | matrix | multidimensional array
Input array, specified as vector, a matrix, or a multidimensional array.
Data Types: double
| single
| int8
| int16
| int32
| int64
| uint8
| uint16
| uint32
| uint64
| logical
Complex Number Support: Yes
B
— Second input array
vector | matrix | multidimensional array
Second input array, specified as a vector, a matrix, or a multidimensional
array to convolve with A
. The array B
does
not have to be the same size as A
.
Data Types: double
| single
| int8
| int16
| int32
| int64
| uint8
| uint16
| uint32
| uint64
| logical
Complex Number Support: Yes
shape
— Subsection of convolution
'full'
(default) | 'same'
| 'valid'
Subsection of the convolution, specified as one of these values:
'full'
— Return the full N-D convolution.'same'
— Return the central part of the convolution, which is the same size asA
.'valid'
— Return only parts of the convolution that are computed without zero-padded edges.
Output Arguments
C
— N-D convolution
vector | matrix | multidimensional array
N-D convolution, returned as a vector, a matrix, or a multidimensional
array. If A
and B
have the same
number of dimensions, the full convolution C = convn(A,B)
has
size size(A)+size(B)-1
.
When one or both of A
and B
are
of type single
, then the output is of type single
.
Otherwise, convn
converts inputs to type double
and
returns type double
.
Data Types: double
| single
More About
N-D Convolution
For discrete, N-dimensional variables A and B, the following equation defines the convolution of A and B:
Each ki runs over all values that lead to legal subscripts of A and B.
Extended Capabilities
Tall Arrays
Calculate with arrays that have more rows than fit in memory.
Usage notes and limitations:
If
shape
is'full'
(default), then the inputsA
andB
must not be empty and only one them can be a tall array.If
shape
is'same'
or'valid'
, thenB
cannot be a tall array.
For more information, see Tall Arrays.
C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.
Thread-Based Environment
Run code in the background using MATLAB® backgroundPool
or accelerate code with Parallel Computing Toolbox™ ThreadPool
.
This function fully supports thread-based environments. For more information, see Run MATLAB Functions in Thread-Based Environment.
GPU Arrays
Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.
This function fully supports GPU arrays. For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).
Distributed Arrays
Partition large arrays across the combined memory of your cluster using Parallel Computing Toolbox™.
This function fully supports distributed arrays. For more information, see Run MATLAB Functions with Distributed Arrays (Parallel Computing Toolbox).
Version History
Introduced before R2006a
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