Computes the convolution of two sequences.
A Boolean that specifies whether to reset the internal state of the node.
True | Resets the internal state of the node. |
False | Does not reset the internal state of the node. |
This input is available when either of the input sequences is a double-precision, floating-point number, a waveform, or an array of waveforms.
Default: False
Length of each set of x-values. This node computes each set of values separately.
sample length x must be greater than 0.
This input is available only if x is a double-precision, floating-point number.
Default: 100
Length of each set of y-values. This node computes each set of values separately.
sample length y must be greater than 0.
This input is available only if y is a double-precision, floating-point number.
Default: 100
The convolution method to use.
This input is available only if x and y are waveforms or arrays.
If x and y are small, the direct method typically is faster. If x and y are large, the frequency domain method typically is faster. Additionally, slight numerical differences can exist between the two methods.
Name | Description |
---|---|
frequency domain | Computes the convolution using an FFT-based technique. |
direct | Computes the convolution using the direct method of linear convolution. |
Computing 1D Convolution with the Frequency Domain Method
When algorithm is frequency domain, this node completes the following steps to compute the linear convolution:
Computing 2D Convolution with the Frequency Domain Method
When algorithm is frequency domain, this node completes the following steps to compute the two-dimensional convolution:
Computing 1D Convolution with the Direct Method
When algorithm is direct, this node uses the following equation to perform the discrete implementation of the linear convolution and obtain the elements of x * y.
for i = 0, 1, 2, ... , M+N-2
where
and
Computing 2D Convolution with the Direct Method
When algorithm is direct, this node uses the following equation to compute the two-dimensional convolution of the input matrices x and y.
for i = 0, 1, 2, ... , M_{1}+M_{2}-2 and j = 0, 1, 2, ... , N_{1}+N_{2}-2
where
and
Default: frequency domain
Size of the convolution of the input sequences.
This input is available only if x and y are 2D arrays.
Name | Description |
---|---|
full | Sets the width of the convolution to one less than the sum of the widths of the input sequences. Sets the height of the convolution to one less than the sum of the heights of the input sequences. |
size X | Sets the width and height of the convolution to the width and height of the first input sequence. |
compact | Sets the width of the convolution to one greater than the difference of the widths of the input sequences. Sets the height of the convolution to one greater than the difference of the heights of the input sequences. The width and height of the first input sequence must be greater than or equal to the width and height of the second input sequence, respectively. |
Default: full
Delays the result of the convolution by half the length of y.
True | Delays the result of the convolution by 0.5 * N * dt where N is the number of elements in y and dt is from x. |
False | Does not delay the result of the convolution. |
This input is available when x is a waveform or an array of waveforms and y is an array of double-precision, floating-point numbers .
Default: False
Error conditions that occur before this node runs.
The node responds to this input according to standard error behavior.
Standard Error Behavior
Many nodes provide an error in input and an error out output so that the node can respond to and communicate errors that occur while code is running. The value of error in specifies whether an error occurred before the node runs. Most nodes respond to values of error in in a standard, predictable way.
Default: No error
A Boolean that specifies whether to use the data points before the current block to compute the convolution.
True | Uses the data points before the current block to compute the convolution. |
False | Does not use the data points before the current block to compute the convolution. |
This input is available only if one of the input sequences is a double-precision, floating-point number.
Default: True
Error information.
The node produces this output according to standard error behavior.
Standard Error Behavior
Many nodes provide an error in input and an error out output so that the node can respond to and communicate errors that occur while code is running. The value of error in specifies whether an error occurred before the node runs. Most nodes respond to values of error in in a standard, predictable way.
The linear convolution of the signals x(t) and y(t) is defined as:
where the symbol * denotes linear convolution.
This node computes the linear convolution, not the circular convolution. However, because $x\left(t\right)*{y\left(t\right)}_{N}\iff X\left(f\right)Y\left(f\right)$ is a Fourier transform pair, where $x\left(t\right)*{y\left(t\right)}_{N}$ is the circular convolution of x(t) and y(t), you can create a circular version of the convolution.
Where This Node Can Run:
Desktop OS: Windows
FPGA: This product does not support FPGA devices