CorrelationFract32

Overview

Computes the zero-lag cross correlation

Discussion

This module calculates the cross correlation of 2 single-channel inputs. The calcuation is block based and the module outputs a single value which is the correlation for the block of input data. The cross correlation is without time lag. The formula is:

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norm(in1,NORM_TYPE) * norm(in2,NORM_TYPE)

NORM_TYPE (Tunable parameter) chooses between L1 norm or L2 norm. L1 norm is the Manhattan distance of a vector. L2 norm (Euclidean) is the Pythagorean distance of a vector.

Type Definition

CODE

typedef struct _ModuleCorrelationFract32
{
    ModuleInstanceDescriptor instance;            // Common Audio Weaver module instance structure
    INT32 norm;                                   // Type of norm: L1_norm=1, L2_norm=2
} ModuleCorrelationFract32Class;

Variables

Properties

Name	Type	Usage	isHidden	Default value	Range	Units
norm	int	parameter	0	2	1:2

Pins

Input Pins

Name: in1

Description: Signal input 1

Data type: fract32

Channel range: 1

Block size range: Unrestricted

Sample rate range: Unrestricted

Complex support: Real

Name: in2

Description: Signal input 2

Data type: fract32

Channel range: 1

Block size range: Unrestricted

Sample rate range: Unrestricted

Complex support: Real

Output Pins

Name: out

Description: xcorrelation value

Data type: fract32

MATLAB Usage

File Name: correlation_fract32_module.m

CODE

 M=correlation_fract32_module(NAME)
 This module calculates the cross correlation of 2 single-channel inputs.
 The cross correlation is without time lag.
 The formula is:   
                      
     -----------------------------------------------
        norm(in1,NORM_TYPE) * norm(in2,NORM_TYPE)
 NORM_TYPE (Tunable parameter) chooses between L1 norm or L2 norm.
 L1 norm is the 'manhattan' distance of a vector
 L2 norm (Euclidean) is the Pythagorean distance of a vector
 Arguments:
    NAME - name of the module.