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# xcov

Computes discrete auto or cross covariance

### Calling Sequence

[c [,lagindex]] = xcov(x [,maxlags [,scaling]]) [c [,lagindex]] = xcov(x,y [,maxlags [,scaling]])

### Parameters

- x
a vector of real or complex floating point numbers.

- y
a vector of real or complex floating point numbers. The default value is

`x`

.- maxlags
a scalar with integer value greater than 1. The default value is

`n`

. Where`n`

is the maximum of the`x`

and`y`

vector length.- scaling
a character string with possible value:

`"biased"`

,`"unbiased"`

,`"coeff"`

,`"none"`

. The default value is`"none"`

.- c
a vector of real or complex floating point numbers with same orientation as

`x`

.- lagindex
a row vector, containing the lags index corresponding to the

`c`

values.

### Description

`c=xcov(x)`

computes the un-normalized discrete covariance: and return in`c`

the sequence of covariance lags with`n`

is the length of`x`

`xcov(x,y)`

computes the un-normalized discrete cross covariance: and return in`c`

the sequence of cross covariance lags with`n`

is the maximum of`x`

and`y`

length's.

If the `maxlags`

argument is given
`xcov`

returns in `c`

the sequence of
covariance lags . If
`maxlags`

is greater than `length(x)`

,
the first and last values of `c`

are zero.

The `scaling`

argument decribes how
is normalized before being returned in
`c`

:

- "biased":
`c=`

`/n`

. - "unbiased":
`c=`

`./(n-(-maxlags:maxlags))`

. - "coeff":
`c=`

`/(norm(x)*norm(y))`

.

### Remark

The corr function computes the "biased" covariance of`x`

and
`y`

and only return in
`c`

the sequence of covariance lags
.### Method

This function computes using`xcorr(x-mean(x),y-mean(y),...)`

.### Examples

### Authors

- Serge Steer, INRIA

### Used Functions

### History

Version | Description |

5.4.0 | xcov added. |

## Comments

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