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# mean() - Signal Processing

```M = mean(A) returns
the mean of the elements
of A along the first array dimension whose size
does not equal 1.If A is a vector, then mean(A) returns
the mean of the elements.If A is a matrix, then mean(A) returns
a row vector containing the mean of each column.If A is a multidimensional array,
then mean(A) operates along the first array dimension
whose size does not equal 1, treating the elements as vectors. This
dimension becomes 1 while the sizes of all other
dimensions remain the same.exampleM = mean(A,dim) returns
the mean along dimension dim. For example,  if A is
a matrix, then mean(A,2) is a column vector containing
the mean of each row.exampleM = mean(___,outtype) returns
the mean with a specified data type, using any of the input arguments
in the previous syntaxes. outtype can be 'default', 'double',
or 'native'.exampleM = mean(___,nanflag) specifies
whether to include or omit NaN values from the
calculation for any of the previous syntaxes. mean(A,'includenan') includes
all NaN values in the calculation while mean(A,'omitnan') ignores
them.```

### Syntax

`M = mean(A) exampleM = mean(A,dim) exampleM = mean(___,outtype) exampleM = mean(___,nanflag) example`

### Example

```Mean of Matrix ColumnsOpen This ExampleCreate a matrix and compute the mean of each column.A = [0 1 1; 2 3 2; 1 3 2; 4 2 2]

A =

0     1     1
2     3     2
1     3     2
4     2     2

M = mean(A)

M =

1.7500    2.2500    1.7500

Mean of Matrix RowsOpen This ExampleCreate a matrix and compute the mean of each row.A = [0 1 1; 2 3 2]

A =

0     1     1
2     3     2

M = mean(A,2)

M =

0.6667
2.3333

Mean of 3-D ArrayOpen This ExampleCreate a 4-by-2-by-3 array of integers between 1 and 10 and compute the mean values along the second dimension.A = gallery('integerdata',10,[4,2,3],1);
M = mean(A,2)

M(:,:,1) =

9.5000
6.5000
9.5000
6.0000

M(:,:,2) =

1.5000
4.0000
7.5000
7.5000

M(:,:,3) =

7.0000
2.5000
4.0000
5.5000

Mean of Single-Precision ArrayOpen This ExampleCreate a single-precision vector of ones and compute its single-precision mean.A = single(ones(10,1));
M = mean(A,'native')

M =

1

The result is also in single precision.class(M)

ans =

single

Mean Excluding NaNOpen This ExampleCreate a vector and compute its mean, excluding NaN values.A = [1 0 0 1 NaN 1 NaN 0];
M = mean(A,'omitnan')

M =

0.5000

If you do not specify 'omitnan', then mean(A) returns NaN.```