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Nonetheless, the white noise model is convenient for situations where the noise spectral density is constant over a frequency range signi cantly larger that the bandwidth of interest in a particular application A white noise process can have any probability distribution; however, the Gaussian distribution is often assumed A key reason is the central limit theorem If the analyst carefully constructs a model accounting for all known or predictable e ects, then the remaining stochastic signals can often be accurately modeled as the output of a linear system that is driven by a Gaussian white noise input This technique will be discussed in Section 45 In this book, the notation N (0, 2 ) will sometimes be used to describe a continuous-time, Gaussion, white-noise process In this case, 2 is interpreted as the PSD, not the variance 2 Reasoning through the units of the symbol v often causes confusion This can be considered from two perspectives First, from the PSD per2 spective, v represents the power per unit frequency interval Therefore, 2 the units of v are the units of v squared divided by the unit of frequency Hz Second, from the perspective of correlation, Rv has the units of v

tell the application id "comappleitunes" with timeout of 1200 seconds try set three_star_songs to every track of playlist "Library" whose rating is 60 repeat with this_song in three_star_songs set song_details to "Song:" & tab & name of this_song & return & "Artist:" & tab & artist of this_song & return & "Album:" & tab & album of this_song & return & "Played:" & tab & played count of this_song & return & "Added:" & tab & date added of this_song end repeat end try end timeout end tell

1 squared and the Dirac delta function ( ) has units of Hz = sec ; there2 fore, v has dimensions corresponding to the square of the units of v times 2 sec For example, if v is an angular rate in deg , then v has dimensions sec 2 deg sec sec deg / sec Hz

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less than the duration of the song, as shown in boldface here:

2 Sv (j ) = v for all [ , ]

tell the application id "comappleitunes" with timeout of 1200 seconds try set three_star_songs to every track of playlist "Library" whose rating is 60 repeat with this_song in three_star_songs set song_details to "Song:" & tab & name of this_song & return & "Artist:" & tab & artist of this_song & return & "Album:" & tab & album of this_song & return & "Played:" & tab & played count of this_song & return & "Added:" & tab & date added of this_song set song_length to (duration of this_song) - 2 end repeat end try end timeout end tell

.

(437)

displays the song s information stored in the song_details variable and provides buttons for rating the song with two stars, rating it with four stars, and canceling Set the dialog box to give up after the length of time specified by the song_length variable,

The Kronecker delta function is dimensionless The dimensions of v are the same as the dimensions of v Discrete-time white noise is physically realizable The power is nite, because the integral of the PSD is only over the discrete-frequency range [ , ]

As will be discussed in Section 49 and 7, navigation systems can often be designed in such a way as to allow performance analysis based on linear systems with stochastic inputs Therefore, this section considers the statistical properties of the output of a linear system when the system model is known and the input is white The results of this section are often used to model error components with signi cant time correlation via the state augmentation approach In such situations, linear stochastic systems forced by Gaussian white noise are of special interest Careful selection of the linear system and white noise statistics can often yield an output stochastic process with statistics matching those of the time correlated error process Examples of such processes are further discussed in Section 463 The output y(t) of a (deterministic) time-invariant, causal, linear system with (stochastic) input w(t) is

so that the dialog box remains displayed until two seconds before the end of the song if the user doesn t click any of the buttons The new statements appear in boldface here:

y(t) =

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