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SignalProcessing

 GenerateGaussian
 generate samples of a Gaussian random signal

 Calling Sequence GenerateGaussian(n, mean, stddev)

Parameters

 n - posint, number of samples mean - realcons, mean of the Gaussian distribution stddev - realcons, standard deviation of the Gaussian distribution

Options

 • container : Array, predefined Array for holding results
 • seed : nonnegint, seed for the pseudo-random number generator

Description

 • The GenerateGaussian( n, mean, stddev, seed ) command generates n floating-point samples for a random signal with a Gaussian distribution of mean mean and with standard deviation stddev. The results are returned in an Array with datatype float.
 • If the container=C option is provided, then the results are put into C and C is returned. With this option, no additional memory is allocated to store the result. The container must be an Array of size n having datatype float.
 • If the seed option is provided, the given value is used as the seed for the pseudo-random number generator.

 • The SignalProcessing[GenerateGaussian] command is thread-safe as of Maple 17.

Examples

 > $\mathrm{with}\left(\mathrm{SignalProcessing}\right):$
 > $\mathrm{GenerateGaussian}\left(10,0,0.3\right)$
 $\left[\begin{array}{cccccccccc}{0.0495371873413880}& {-0.0661056974615050}& {0.354875385184704}& {-1.01149036815709}& {0.288902907818768}& {-0.0812277011514116}& {0.587902082619449}& {0.384853190715920}& {0.0884179640721524}& {-0.105533578711158}\end{array}\right]$ (1)
 > $c≔\mathrm{Array}\left(1..10,'\mathrm{datatype}'={'\mathrm{float}'}_{8},'\mathrm{order}'='\mathrm{C_order}'\right):$
 > $\mathrm{GenerateGaussian}\left(10,0,0.3,'\mathrm{container}'=c\right)$
 $\left[\begin{array}{cccccccccc}{0.193439942966902}& {0.432921279364566}& {-0.00923099297886446}& {-0.0525675926806905}& {-0.283722360626343}& {-0.254513167668344}& {-0.278375701180750}& {0.0309625011601432}& {-0.262806836671345}& {0.350352787464058}\end{array}\right]$ (2)
 > $c$
 $\left[\begin{array}{cccccccccc}{0.193439942966902}& {0.432921279364566}& {-0.00923099297886446}& {-0.0525675926806905}& {-0.283722360626343}& {-0.254513167668344}& {-0.278375701180750}& {0.0309625011601432}& {-0.262806836671345}& {0.350352787464058}\end{array}\right]$ (3)
 > $\mathrm{SignalPlot}\left(c\right)$ Compatibility

 • The SignalProcessing[GenerateGaussian] command was introduced in Maple 17.