y = rms(x)
y = rms(x, dim)
y = rms(x, vecdim)
y = rms(x, 'all')
y = rms(x, dim, type)
y = rms(x, 'all', type)
y = rms(x, dim, type, nanflag)
y = rms(x, 'all', type, nanflag)
| Parameter | Description |
|---|---|
| x | Input array, specified as a vector, matrix, or multidimensional array: single, double, logical, integer types |
| dim | Dimension to operate along, specified as a positive integer scalar. |
| 'all' | Operate on all elements of x, returning the RMS value of all elements. |
| type | Data type to use in the computation: 'double', 'native' |
| nanflag | Missing value condition, specified as: 'includenan', 'includemissing', 'omitnan', 'omitmissing' |
| Parameter | Description |
|---|---|
| y | Root mean square value(s), returned as a scalar, vector, or array. |
rms returns the root mean square (RMS) value of the input array elements.
The root mean square value of an array x is:$$\mathrm{RMS}(x) = \sqrt{ \frac{1}{N} \sum_{n=1}^{N} |x_n|^2 }$$where the summation is performed along the specified dimension(s), and N is the number of elements along those dimensions.
NaN Handling: By default, NaN values are included. Use 'omitnan' or 'omitmissing' to ignore NaNs.
Type Handling: If type is 'native', the computation and output use the same class as the input (e.g., integer input returns integer output).
t = 0:0.001:1-0.001;
x = cos(2*pi*100*t);
y = rms(x)
% y = 0.7071
x = [4 -5 1; 2 3 5; -9 1 7];
y = rms(x)
% y = [5.8023 3.4157 5.0000]
x = [6 4 23 -3; 9 -10 4 11; 2 8 -5 1];
y = rms(x,2)
% y = [12.1450; 8.9163; 4.8477]
x = [1.77 -0.005 nan -2.95; nan 0.34 nan 0.19];
y = rms(x,"omitnan")
% y = [1.7700 0.2404 nan 2.0903]
M = uint8([10:30:70;20:30:80;30:30:90]);
R = rms(M, 'native')
% R is of class uint8
| Version | Description |
|---|---|
| 1.16.0 | initial version |