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c = mean(a)
c = mean(a,dim)
c = mean(a) computes the mean value of the fixed-point array a along its first nonsingleton dimension.
c = mean(a,dim) computes the mean value of the fixed-point array a along dimension dim. dim must be a positive, real-valued integer with a power-of-two slope and a bias of 0.
The input to the mean function must be a real-valued fixed-point array.
The fixed-point output array c has the same numerictype properties as the fixed-point input array a and has no local fimath.
When a is an empty fixed-point array (value = []), the value of the output array is zero.
Compute the mean value along the first dimension (rows) of a fixed-point array.
x = fi([0 1 2; 3 4 5], 1, 32); % x is a signed FI object with a 32-bit word length % and a best-precision fraction length of 28-bits mx1 = mean(x,1)
Compute the mean value along the second dimension (columns) of a fixed-point array.
x = fi([0 1 2; 3 4 5], 1, 32); % x is a signed FI object with a 32-bit word length % and a best-precision fraction length of 28 bits mx2 = mean(x,2)
The general equation for computing the mean of an array a, across dimension dim is:
sum(a,dim)/size(a,dim)
Because size(a,dim) is always a positive integer, the algorithm casts size(a,dim) to an unsigned 32-bit fi object with a fraction length of zero (SizeA). The algorithm then computes the mean of a according to the following equation, where Tx represents the numerictype properties of the fixed-point input array a:
c = Tx.divide(sum(a,dim), SizeA)

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