Overview

Cross correlation function

Discussion

This module computes the deterministic cross correlation of the signals on its input pins a block at a time. It is very similar to convolution, differing only in the order of the output. The output is computed by $s[n] = \sum_{k=0}^{M-1} x[n+k] y[k]$, where $x[n]$ is on pin 1 with length $M$ and $y[n]$ is on pin 2, also of length $M$. This operation could be generalized to allow different block sizes if needed.

The parameters shape, skip and length allows control of the range of $n$ that gets calculated. Shape is for quick setting of common ranges. shape = 0: sets skip=0, olen=2*M-1 to compute the full correlation shape = 1: sets skip=M/2, olen=M to compute the center part that has the same length as the inputs. shape = 2: leaves skip and olen to be user-defined. skip: starts storing output at $n = \mathit{skip}$ olen: writes only this many output samples, so $\mathit{skip} <= n < \mathit{skip} + \mathit{olen}$.

Type Definition

typedef struct _ModuleCorrelate
{
    ModuleInstanceDescriptor instance;            // Common Audio Weaver module instance structure
    INT32 shape;                                  // Shape of subset to calculate
    INT32 skip;                                   // Number of samples of full cross correlation to skip at output
    INT32 olen;                                   // Length of output
} ModuleCorrelateClass;

Variables

Properties

Pins

Input Pins

Name: in0

Description: Input signal 0

Data type: float

Channel range: Unrestricted

Block size range: Unrestricted

Sample rate range: Unrestricted

Complex support: Real

Name: in1

Description: Input signal 1

Data type: float

Channel range: Unrestricted

Block size range: Unrestricted

Sample rate range: Unrestricted

Complex support: Real

Output Pins

Name: out

Description: Cross correlation output

Data type: float

MATLAB Usage

File Name: correlate_module.m

 M = correlate_module(NAME, SHAPE)
 This module implements a partial correlation of the two signals on its
 input pins. How much of the correlation to write can be controlled by
 the parameters. Also see convolve_module, which is very similar.
 Arguments:
   NAME - name of the module
   SHAPE - enum of standard subset to calculate