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# mean() - Signal Processing

### Syntax

### Example

### Output / Return Value

### Limitations

### Alternatives / See Also

### Reference

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.

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