09-18-2014
Do you mean use standard deviation to identify "outliers"? That is usually the accepted approach - 3 stddev from the mean.
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LEARN ABOUT OPENSOLARIS
mlib_signalgaussnoiseinit_s16
mlib_SignalGaussNoiseInit_S16(3MLIB) mediaLib Library Functions mlib_SignalGaussNoiseInit_S16(3MLIB)
NAME
mlib_SignalGaussNoiseInit_S16 - Gaussian noise generation
SYNOPSIS
cc [ flag... ] file... -lmlib [ library... ]
#include <mlib.h>
mlib_status mlib_SignalGaussNoiseInit_S16(void **state, mlib_s16 mag,
mlib_f32 mean, mlib_f32 stddev, mlib_s16 seed);
DESCRIPTION
The mlib_SignalGaussNoiseInit_S16() function allocates memory for an internal state structure and converts the parameters into an internal
representation.
PARAMETERS
The function takes the following arguments:
state Internal state structure.
mag Magnitude of the Gaussian noise to be generated, in Q15 format.
mean Mean of the Gaussian noise.
stddev Standard deviation of the Gaussian noise.
seed Seed value for the pseudorandom number generator.
RETURN VALUES
The function returns MLIB_SUCCESS if successful. Otherwise it returns MLIB_FAILURE.
ATTRIBUTES
See attributes(5) for descriptions of the following attributes:
+-----------------------------+-----------------------------+
| ATTRIBUTE TYPE | ATTRIBUTE VALUE |
+-----------------------------+-----------------------------+
|Interface Stability |Committed |
+-----------------------------+-----------------------------+
|MT-Level |MT-Safe |
+-----------------------------+-----------------------------+
SEE ALSO
mlib_SignalGaussNoise_S16(3MLIB), mlib_SignalGaussNoiseFree_S16(3MLIB), attributes(5)
SunOS 5.11 2 Mar 2007 mlib_SignalGaussNoiseInit_S16(3MLIB)