convolve1

Convolution Integral for one dimensional data. More...

Functions
AFAPI array	convolve1 (const array &signal, const array &filter, const convMode mode=AF_CONV_DEFAULT, const convDomain domain=AF_CONV_AUTO)
	C++ Interface for convolution on one dimensional signals. More...
AFAPI array	fftConvolve1 (const array &signal, const array &filter, const convMode mode=AF_CONV_DEFAULT)
	C++ Interface for convolution on 1D signals using FFT. More...
AFAPI af_err	af_convolve1 (af_array *out, const af_array signal, const af_array filter, const af_conv_mode mode, af_conv_domain domain)
	C Interface for convolution on one dimensional signals. More...
AFAPI af_err	af_fft_convolve1 (af_array *out, const af_array signal, const af_array filter, const af_conv_mode mode)
	C Interface for convolution on 1D signals using FFT. More...

Detailed Description

Convolution Integral for one dimensional data.

A convolution is a common operation between a source array, a, and a filter (or kernel) array b. The answer to the convolution is the same as computing the coefficients in polynomial multiplication, if a and b are the coefficients.

Another way to think about it is that the filter kernel is centered on each pixel in a, and the output for that pixel or data point is the sum of the products.

Depending on the size of the signal and the filter, any one of the following batch mode convolutions take place.

• No Batch - Single filter applied to single input.
• Filter is Batched - Many filters applied on same input
• Signal is Batched - Single filter applied to a set of inputs.
• Identical Batches - A set of filters applied onto to a set of inputs in one-to-one correspondence.
• Non overlapping Batches - All batched filters are applied to all batched signals. The batch axis of Signal and Filter should not be the same.

Note

All non-overlapping(interleaved) convolutions default to frequency domain AF_CONV_FREQ irrespective of the provided convolution mode argument.

For one dimensional signals (lets say m is size of 0th axis), below batch operations are possible.

Signal Size	Filter Size	Output Size	Batch Mode	Description
\( [m \ 1 \ 1 \ 1] \)	\( [m \ 1 \ 1 \ 1] \)	\( [m \ 1 \ 1 \ 1] \)	No Batch	Output will be a single convolved array
\( [m \ 1 \ 1 \ 1] \)	\( [m \ n \ 1 \ 1] \)	\( [m \ n \ 1 \ 1] \)	Filter is Batched	n filters applied to same input
\( [m \ n \ 1 \ 1] \)	\( [m \ 1 \ 1 \ 1] \)	\( [m \ n \ 1 \ 1] \)	Signal is Batched	1 filter applied to n inputs
\( [m \ n \ p \ q] \)	\( [m \ n \ p \ q] \)	\( [m \ n \ p \ q] \)	Identical Batches	n*p*q filters applied to n*p*q inputs in one-to-one correspondence
\( [m \ n \ 1 \ 1] \)	\( [m \ 1 \ p \ q] \)	\( [m \ n \ p \ q] \)	Non-overlapping batches	p*q filters applied to n inputs to produce n x p x q results

There are various other permutations of signal and filter sizes that fall under the category of non-overlapping batch mode that are not listed in the above table. For any signal and filter size combination to fall under the non-overlapping batch mode, they should satisfy one of the following conditions.

• Signal and filter size along a given batch axis ( \( > 1 \)) should be same.
• Either signal size or filter size along a given batch axis ( \( > 1 \)) should be equal to one.

Note

For the above tabular illustrations, we assumed af_conv_mode is AF_CONV_DEFAULT.

Function Documentation

af_convolve1()

AFAPI af_err af_convolve1	(	af_array *	out,
		const af_array	signal,
		const af_array	filter,
		const af_conv_mode	mode,
		af_conv_domain	domain
	)

C Interface for convolution on one dimensional signals.

Parameters

[out]	out	is convolved array
[in]	signal	is the input signal
[in]	filter	is the signal that shall be flipped for the convolution operation
[in]	mode	indicates if the convolution should be expanded or not(where output size equals input)
[in]	domain	specifies if the convolution should be performed in frequency os spatial domain

Returns

AF_SUCCESS if the convolution is successful, otherwise an appropriate error code is returned.

Note

The default parameter of domain, AF_CONV_AUTO, heuristically switches between frequency and spatial domain.

af_fft_convolve1()

AFAPI af_err af_fft_convolve1	(	af_array *	out,
		const af_array	signal,
		const af_array	filter,
		const af_conv_mode	mode
	)

C Interface for convolution on 1D signals using FFT.

Parameters

[out]	out	is convolved array
[in]	signal	is the input signal
[in]	filter	is the signal that shall be used for the convolution operation
[in]	mode	indicates if the convolution should be expanded or not(where output size equals input)

Returns

AF_SUCCESS if the convolution is successful, otherwise an appropriate error code is returned.

convolve1()

AFAPI array convolve1	(	const array &	signal,
		const array &	filter,
		const convMode	mode = AF_CONV_DEFAULT,
		const convDomain	domain = AF_CONV_AUTO
	)

C++ Interface for convolution on one dimensional signals.

    // vector<dim4> numDims;
    // vector<vector<float> > in;
    array signal(numDims[0], &(in[0].front()));
    // signal dims = [32 1 1 1]
    array filter(numDims[1], &(in[1].front()));
    // filter dims = [4 1 1 1]
 
    array output = convolve1(signal, filter, AF_CONV_DEFAULT);
    // output dims = [32 1 1 1] - same as input since expand(3rd argument is
    // false) None of the dimensions > 1 has lenght > 1, so no batch mode is
    // activated.

Parameters

[in]	signal	is the input signal
[in]	filter	is the signal that shall be flipped for the convolution operation
[in]	mode	indicates if the convolution should be expanded or not(where output size equals input)
[in]	domain	specifies if the convolution should be performed in frequency os spatial domain

Returns

the convolved array

Note

The default parameter of domain, AF_CONV_AUTO, heuristically switches between frequency and spatial domain.

fftConvolve1()

AFAPI array fftConvolve1	(	const array &	signal,
		const array &	filter,
		const convMode	mode = AF_CONV_DEFAULT
	)

C++ Interface for convolution on 1D signals using FFT.

Parameters

[in]	signal	is the input signal
[in]	filter	is the signal that shall be used for the convolution operation
[in]	mode	indicates if the convolution should be expanded or not(where output size equals input)

Returns

the convolved array