WOLFRAM SYSTEM MODELER
ContinuousMeanCalculates the empirical expectation (mean) value of its input signal |
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Wolfram Language
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SystemModel["Modelica.Blocks.Math.ContinuousMean"]
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Information
This information is part of the Modelica Standard Library maintained by the Modelica Association.
This block continuously calculates the mean value of its input signal. It uses the function:
integral( u over time)
y = ------------------------
time - startTime
This can be used to determine the empirical expectation value of a random signal, such as generated by the Noise blocks.
The parameter t_eps is used to avoid large fluctuations but can be set to zero (the mean value computation starts at <simulation start time> but is only returned after an additional t_eps and before that time instant y = u).
See also the Mean block for a sampled implementation.
This block is demonstrated in the examples UniformNoiseProperties and NormalNoiseProperties.
Parameters (2)
| t_eps |
Value: 1e-7 Type: Time (s) Description: Mean value calculation starts at startTime + t_eps |
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| startTime |
Value: -Modelica.Constants.inf Type: Real Description: Starting point for mean if after simulation start-point |
Connectors (2)
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u |
Type: RealInput Description: Noisy input signal |
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y |
Type: RealOutput Description: Expectation (mean) value of the input signal |
Used in Examples (2)
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Modelica.Blocks.Examples.Noise Demonstrates the computation of properties for uniformly distributed noise |
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Modelica.Blocks.Examples.Noise Demonstrates the computation of properties for normally distributed noise |
Revisions
| Date | Description | ||
|---|---|---|---|
| June 13, 2023 | Hans Olsson. Avoid almost singularity for integrators. | ||
| June 22, 2015 |
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