Random input signal

Use a `frest.Random`

object to represent a random input signal
for frequency response estimation. The random signal contains uniformly distributed random
numbers in the interval `[0 Amplitude]`

or `[Amplitude 0]`

for positive and negative amplitudes, respectively.

Random signals are useful because they can excite the system uniformly at all frequencies up to the Nyquist frequency.

You can use a random input signal for estimation at the command line, in the **Linear
Analysis Tool**, or with the Frequency Response Estimator block. The
estimation algorithm injects the sinestream signal at the input point you specify for
estimation, and measures the response at the output point.

When you use a random input signal for estimation, the frequencies returned in the
estimated `frd`

model depend on the length and sampling time of the signal.
They are the frequencies obtained in the fast Fourier transform of the input signal. For more
information, see the Algorithm section of `frestimate`

.

To view a plot of your input signal, type `plot(input)`

. To create a
`timeseries`

object for your input signal, use the `generateTimeseries`

command.

creates a random signal with properties based on the dynamics of the linear system
`input`

= frest.Random(`sys`

)`sys`

. For instance, if you have an exact linearization of your
system, you can use it to initialize the parameters.

creates random signal with properties
specified using one or more name-value pairs. Enclose each property name in quotes.`input`

= frest.Random(`Name,Value`

)

`frestimate` | Frequency response estimation of Simulink models |

`generateTimeseries` | Generate time-domain data for input signal |

`frest.simCompare` | Plot time-domain simulation of nonlinear and linear models |

`frest.simView` | Plot frequency response model in time- and frequency-domain |

`getSimulationTime` | Final time of simulation for frequency response estimation |

In the **Linear Analysis Tool**, to use a random input signal for estimation, on
the **Estimation** tab, select **Input Signal** > **Random**.