DSP Blockset

Correlation

Compute the correlation along the columns of two inputs.

Library

Statistics

Description

The Correlation block computes the cross-correlation of corresponding columns (channels) of the M_u-by-N input matrix u and M_v-by-N input matrix v. The frame status of both inputs must be the same. The block does not accept sample-based full-dimension matrix inputs or 2-D row vector inputs. The outputs are always sample-based.

Sections of This Reference Page

• Correlating Frame-Based Inputs
• Correlating Sample-Based Inputs
• Setting the Computation Domain Parameter
• Dialog Box
• Supported Data Types
• See Also

Correlating Frame-Based Inputs

Matrix inputs must be frame-based. The output, y, is a frame-based (M_u+M_v-1)-by-N matrix whose jth column has elements

where * denotes the complex conjugate. Inputs u and v are zero when indexed outside of their valid ranges. When both inputs are real, the output is real; when one or both inputs are complex, the output is complex.

When one input is a column vector (single channel) and the other is a matrix (multiple channels), the single-channel input is independently cross-correlated with each channel of the multichannel input. For example, if u is a M_u-by-1 column vector and v is an M_v-by-N matrix, the output is an (M_u+M_v-1)-by-N matrix whose jth column has elements

Correlating Sample-Based Inputs

Matrix inputs cannot be sample based, so all sample-based inputs are column vectors or 1-D vectors. (the block does not support 2-D row vector inputs.) If u and v are sample-based vectors with lengths M_u and M_v, the Correlation block performs the vector cross-correlation

The dimensions of the sample-based output vector are determined by the dimensions of the input vectors:

• When both inputs are column vectors, or when one input is a column vector and the other is a 1-D vector, the output is a (M_u+M_v-1)-by-1 column vector.
• When both inputs are 1-D vectors, the output is a 1-D vector of length M_u+M_v-1.

The Correlation block does not accept sample-based full-dimension matrix inputs or 2-D row vector inputs.

Setting the Computation Domain Parameter

You must set the domain in which the block computes correlations in the Computation domain parameter. You can select one of the following settings:

• Time -- The block computes in the time domain, which minimizes memory use.
• Frequency -- The block computes in the frequency domain, which may require fewer computations than computing in the time domain (depending on the input length).
• Fastest -- The block computes in the domain that minimizes the number of computations (time domain or frequency domain).

Dialog Box

Computation domain

The domain in which the block computes correlations: Time, Frequency, or Fastest. To minimize memory use, select Time. To minimize the number of computations, select Fastest. For more information, see Setting the Computation Domain Parameter.

Supported Data Types

• Double-precision floating point
• Single-precision floating point

To learn how to convert to the above data types in MATLAB and Simulink, see Supported Data Types and How to Convert to Them.

See Also

Autocorrelation	DSP Blockset
Convolution	DSP Blockset
xcorr	Signal Processing Toolbox

Also see Statistics for a list of all the blocks in the Statistics library.

Convolution

Counter