Cross Correlation VI

Owning Palette: Signal Operation VIs

Requires: Multicore Analysis and Sparse Matrix Toolkit

Computes the cross correlation of the input sequences X and Y.

Wire data to the X input and the Y input to determine the polymorphic instance to use or manually select the instance.

Details  

1D Cross Correlation (DBL)

	X specifies the first input sequence.
	Y specifies the second input sequence.
	algorithm specifies the correlation method to use. When algorithm is Direct, this VI computes the cross correlation using the direct method of linear correlation. When algorithm is Frequency Domain, this VI computes the cross correlation using an FFT-based technique. If X and Y are small, the Direct method typically computes faster than the Frequency Domain method. If X and Y are large, the Frequency Domain method typically computes faster than the Direct method. Slight numerical differences can exist between the two methods. 0 Direct 1 Frequency Domain (default)
	error in describes error conditions that occur before this node runs. This input provides standard error in functionality.
	normalization specifies the normalization method to use to compute the cross correlation of X and Y. 0 None (default) 1 Unbiased 2 Biased
	Rxy returns the cross correlation of X and Y.
	error out contains error information. This output provides standard error out functionality.

1D Cross Correlation (SGL)

	X specifies the first input sequence.
	Y specifies the second input sequence.
	algorithm specifies the correlation method to use. When algorithm is Direct, this VI computes the cross correlation using the direct method of linear correlation. When algorithm is Frequency Domain, this VI computes the cross correlation using an FFT-based technique. If X and Y are small, the Direct method typically computes faster than the Frequency Domain method. If X and Y are large, the Frequency Domain method typically computes faster than the Direct method. Slight numerical differences can exist between the two methods. 0 Direct 1 Frequency Domain (default)
	error in describes error conditions that occur before this node runs. This input provides standard error in functionality.
	normalization specifies the normalization method to use to compute the cross correlation of X and Y. 0 None (default) 1 Unbiased 2 Biased
	Rxy returns the cross correlation of X and Y.
	error out contains error information. This output provides standard error out functionality.

1D Cross Correlation (CDB)

	X specifies the first input sequence.
	Y specifies the second input sequence.
	algorithm specifies the correlation method to use. When algorithm is Direct, this VI computes the cross correlation using the direct method of linear correlation. When algorithm is Frequency Domain, this VI computes the cross correlation using an FFT-based technique. If X and Y are small, the Direct method typically computes faster than the Frequency Domain method. If X and Y are large, the Frequency Domain method typically computes faster than the Direct method. Slight numerical differences can exist between the two methods. 0 Direct 1 Frequency Domain (default)
	error in describes error conditions that occur before this node runs. This input provides standard error in functionality.
	normalization specifies the normalization method to use to compute the cross correlation of X and Y. 0 None (default) 1 Unbiased 2 Biased
	Rxy returns the cross correlation of X and Y.
	error out contains error information. This output provides standard error out functionality.

1D Cross Correlation (CSG)

	X specifies the first input sequence.
	Y specifies the second input sequence.
	algorithm specifies the correlation method to use. When algorithm is Direct, this VI computes the cross correlation using the direct method of linear correlation. When algorithm is Frequency Domain, this VI computes the cross correlation using an FFT-based technique. If X and Y are small, the Direct method typically computes faster than the Frequency Domain method. If X and Y are large, the Frequency Domain method typically computes faster than the Direct method. Slight numerical differences can exist between the two methods. 0 Direct 1 Frequency Domain (default)
	error in describes error conditions that occur before this node runs. This input provides standard error in functionality.
	normalization specifies the normalization method to use to compute the cross correlation of X and Y. 0 None (default) 1 Unbiased 2 Biased
	Rxy returns the cross correlation of X and Y.
	error out contains error information. This output provides standard error out functionality.

2D Cross Correlation (DBL)

	X specifies the first input sequence.
	Y specifies the second input sequence.
	algorithm specifies the correlation method to use. When algorithm is Direct, this VI computes the cross correlation using the direct method of linear correlation. When algorithm is Frequency Domain, this VI computes the cross correlation using an FFT-based technique. If X and Y are small, the Direct method typically computes faster than the Frequency Domain method. If X and Y are large, the Frequency Domain method typically computes faster than the Direct method. Slight numerical differences can exist between the two methods. 0 Direct 1 Frequency Domain (default)
	error in describes error conditions that occur before this node runs. This input provides standard error in functionality.
	Rxy returns the cross correlation of X and Y.
	error out contains error information. This output provides standard error out functionality.

2D Cross Correlation (SGL)

	X specifies the first input sequence.
	Y specifies the second input sequence.
	algorithm specifies the correlation method to use. When algorithm is Direct, this VI computes the cross correlation using the direct method of linear correlation. When algorithm is Frequency Domain, this VI computes the cross correlation using an FFT-based technique. If X and Y are small, the Direct method typically computes faster than the Frequency Domain method. If X and Y are large, the Frequency Domain method typically computes faster than the Direct method. Slight numerical differences can exist between the two methods. 0 Direct 1 Frequency Domain (default)
	error in describes error conditions that occur before this node runs. This input provides standard error in functionality.
	Rxy returns the cross correlation of X and Y.
	error out contains error information. This output provides standard error out functionality.

2D Cross Correlation (CDB)

	X specifies the first input sequence.
	Y specifies the second input sequence.
	algorithm specifies the correlation method to use. When algorithm is Direct, this VI computes the cross correlation using the direct method of linear correlation. When algorithm is Frequency Domain, this VI computes the cross correlation using an FFT-based technique. If X and Y are small, the Direct method typically computes faster than the Frequency Domain method. If X and Y are large, the Frequency Domain method typically computes faster than the Direct method. Slight numerical differences can exist between the two methods. 0 Direct 1 Frequency Domain (default)
	error in describes error conditions that occur before this node runs. This input provides standard error in functionality.
	Rxy returns the cross correlation of X and Y.
	error out contains error information. This output provides standard error out functionality.

2D Cross Correlation (CSG)

	X specifies the first input sequence.
	Y specifies the second input sequence.
	algorithm specifies the correlation method to use. When algorithm is Direct, this VI computes the cross correlation using the direct method of linear correlation. When algorithm is Frequency Domain, this VI computes the cross correlation using an FFT-based technique. If X and Y are small, the Direct method typically computes faster than the Frequency Domain method. If X and Y are large, the Frequency Domain method typically computes faster than the Direct method. Slight numerical differences can exist between the two methods. 0 Direct 1 Frequency Domain (default)
	error in describes error conditions that occur before this node runs. This input provides standard error in functionality.
	Rxy returns the cross correlation of X and Y.
	error out contains error information. This output provides standard error out functionality.

Cross Correlation Details

The following table lists the support characteristics of this VI.

Supported on RT targets	Yes
Suitable for bounded execution times on RT	Yes

Refer to the Details section in the CrossCorrelation VI for more details about this VI.