WOLFRAM SYSTEM MODELER

UniformNoiseProperties

Demonstrates the computation of properties for uniformally distributed noise

Diagram

Wolfram Language

In[1]:=
SystemModel["Modelica.Blocks.Examples.NoiseExamples.UniformNoiseProperties"]
Out[1]:=

Information

This information is part of the Modelica Standard Library maintained by the Modelica Association.

This example demonstrates statistical properties of the Blocks.Noise.UniformNoise block using a uniform random number distribution. Block "noise" defines a band of 0 .. 6 and from the generated noise the mean and the variance is computed with blocks of package Blocks.Math. Simulation results are shown in the next diagram:

The mean value of a uniform noise in the range 0 .. 6 is 3 and its variance is 3 as well. The simulation results above show good agreement (after a short initial phase). This demonstrates that the random number generator and the mapping to a uniform distribution have good statistical properties.

Parameters (5)

y_min

Value: 0

Type: Real

Description: Minimum value of band

y_max

Value: 6

Type: Real

Description: Maximum value of band

pMean

Value: (y_min + y_max) / 2

Type: Real

Description: Theoretical mean value of uniform distribution

var

Value: (y_max - y_min) ^ 2 / 12

Type: Real

Description: Theoretical variance of uniform distribution

std

Value: sqrt(var)

Type: Real

Description: Theoretical standard deviation of uniform distribution

Outputs (2)

meanError_y

Default Value: meanError.y

Type: Real

sigmaError_y

Default Value: sigmaError.y

Type: Real

Components (11)

globalSeed

Type: GlobalSeed

noise

Type: UniformNoise

mean

Type: ContinuousMean

variance

Type: Variance

theoreticalVariance

Type: MultiProduct

meanError

Type: Feedback

theoreticalMean

Type: Constant

varianceError

Type: Feedback

theoreticalSigma

Type: Constant

standardDeviation

Type: StandardDeviation

sigmaError

Type: Feedback

Revisions

Date Description
June 22, 2015
Initial version implemented by A. Klöckner, F. v.d. Linden, D. Zimmer, M. Otter.
DLR Institute of System Dynamics and Control