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DTSTART:20170312T030000
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DTSTAMP:20170528T023555Z
UID:2D52A633-434E-11E7-8752-0050568D2FB3
DTSTART;TZID=Canada/Pacific:20170601T153000
DTEND;TZID=Canada/Pacific:20170601T163000
DESCRIPTION:It is well known and fundamental that the matched filter is the
  optimal detector for a signal immersed in additive white Gaussian noise. 
 The matched filter is a continuous-time structure and always performs bett
 er than digital matched filters\, which are optimal structures for detecti
 ng signals in additive white Gaussian noise based on a number of independe
 nt samples of the signal-plus-noise. In the case of non-Gaussian noise\, o
 nly one other optimal detection structure is known\, and that is the optim
 al (continuous-time) detector for signals immersed in Laplace noise. Meanw
 hile\, the fundamental Gaussian distribution is a special case of the more
  flexible and descriptive generalized Gaussian distribution (GGD). In this
  talk\, we derive the optimal detector for a signal immersed in additive G
 GD noise\, which we dub the generalized matched filter. This detection sch
 eme finds the absolute value of the difference between a replica of the tr
 ansmitted signal and the received signal-plus noise\, raises this absolute
  error to the βth power\, and then integrates the resulting signal. This 
 detection structure can\, therefore\, also be referred to as the absolute 
 error power detector. We show that the matched filter is a special case of
  the absolute error power detector for GGD parameter β = 2\, the Gaussian
  noise case\, and that the optimal detector for Laplace noise is also a sp
 ecial case when β = 1. The optimal probability of error for binary signal
 ling in additive white generalized Gaussian noise is assessed. The fundame
 ntal structure is also optimal for higher-level modulations after straight
 forward extensions.\n\nSpeaker(s): Professor Norman Beaulieu\, \n\nRoom: 1
 101\, Bldg: EME\, UBC Okanagan campus\, Kelowna\, British Columbia\, Canad
 a
LOCATION:Room: 1101\, Bldg: EME\, UBC Okanagan campus\, Kelowna\, British C
 olumbia\, Canada
ORGANIZER:Julian.Cheng@ubc.ca
SEQUENCE:1
SUMMARY:The Absolute Error Power Detectors
URL;VALUE=URI:https://events.vtools.ieee.org/m/45726
X-ALT-DESC:Description: <br /><p>It is well known and fundamental that the 
 matched filter is the optimal detector for a signal immersed in additive w
 hite Gaussian noise. The matched filter is a continuous-time structure and
  always performs better than digital matched filters\, which are optimal s
 tructures for detecting signals in additive white Gaussian noise based on 
 a number of independent samples of the signal-plus-noise. In the case of n
 on-Gaussian noise\, only one other optimal detection structure is known\, 
 and that is the optimal (continuous-time) detector for signals immersed in
  Laplace noise. Meanwhile\, the fundamental Gaussian distribution is a spe
 cial case of the more flexible and descriptive generalized Gaussian distri
 bution (GGD). In this talk\, we derive the optimal detector for a signal i
 mmersed in additive GGD noise\, which we dub the generalized matched filte
 r. This detection scheme finds the absolute value of the difference betwee
 n a replica of the transmitted signal and the received signal-plus noise\,
  raises this absolute error to the &beta\;th power\, and then integrates t
 he resulting signal. This detection structure can\, therefore\, also be re
 ferred to as the absolute error power detector. We show that the matched f
 ilter is a special case of the absolute error power detector for GGD param
 eter &beta\; = 2\, the Gaussian noise case\, and that the optimal detector
  for Laplace noise is also a special case when &beta\; = 1. The optimal pr
 obability of error for binary signalling in additive white generalized Gau
 ssian noise is assessed. The fundamental structure is also optimal for hig
 her-level modulations after straightforward extensions.</p>
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