Variance
Calculates the empirical variance of its input signal
Library
Modelica/Blocks/Math
Description
This block calculates the empirical variance of its input signal. It is based on the formula(but implemented in a more reliable numerical way):
y = mean( (u - mean(u))^2 )
The parameter t_eps is used to guard against division by zero (the variance computationstarts at <simulation start time> + t_eps and before that time instant y = 0).
The variance of a signal is also equal to its mean power.
This block is demonstrated in the examplesUniformNoiseProperties andNormalNoiseProperties.
Parameters
| Name | Label | Description | Data Type | Valid Values |
|---|---|---|---|---|
mo_t_eps | t_eps | Variance calculation starts at startTime + t_eps | Scalar | |
mo_t_0 | t_0 | Start time | Scalar |
| Name | Label | Description | Data Type | Valid Values |
|---|---|---|---|---|
mo__nmodifiers | Number of Modifiers | Specifies the number of modifiers | Number | |
mo__modifiers | Modifiers | Add new modifier | Structure | |
mo__modifiers/varname | Variable name | Cell of strings | 'mu' | |
mo__modifiers/attribute | Attribute | Cell of strings | 'start' | |
mo__modifiers/value | Value |
Ports
| Name | Type | Description | IO Type | Number |
|---|---|---|---|---|
u | implicit | Noisy input signal | input | 1 |
y | implicit | Variance of the input signal | output | 1 |