Abstract
A class of nonlinear receiver structures is described for the detection of weak signals in non-Gaussian narrowband noise. In particular, the concept of a locally optimum receiver structure is extended to the case of narrowband signal and noise models. A useful class of non-Gaussian narrowband signal and noise models. A useful class of non-Gaussian narrowband noise models is developed for which the locally optimum receiver implementation is explicitly determined. These structure are shown to provide considerable improvement over conventional linear receiver structures. The basis of comparison is taken as the asymptotic relative efficiency (ARE). Unfortunately, the locally optimum receiver requires explicit a priori knowledge of the underlying noise distribution. To circumvent this difficulty a rather simple adaptive nonlinear receiver structure is described which attempts to adapt to the unknown prevailing noise environment.
| Original language | English |
|---|---|
| Pages (from-to) | 592-600 |
| Number of pages | 9 |
| Journal | IEEE Transactions on Information Theory |
| Volume | IT-25 |
| Issue number | 5 |
| State | Published - Sep 1 1979 |
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ASJC Scopus subject areas
- Information Systems
- Electrical and Electronic Engineering
Cite this
DETECTION OF WEAK SIGNALS IN NARROWBAND NON-GAUSSIAN NOISE. / Modestino, James W.; Ningo, Aaron Y.
In: IEEE Transactions on Information Theory, Vol. IT-25, No. 5, 01.09.1979, p. 592-600.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - DETECTION OF WEAK SIGNALS IN NARROWBAND NON-GAUSSIAN NOISE.
AU - Modestino, James W.
AU - Ningo, Aaron Y.
PY - 1979/9/1
Y1 - 1979/9/1
N2 - A class of nonlinear receiver structures is described for the detection of weak signals in non-Gaussian narrowband noise. In particular, the concept of a locally optimum receiver structure is extended to the case of narrowband signal and noise models. A useful class of non-Gaussian narrowband signal and noise models. A useful class of non-Gaussian narrowband noise models is developed for which the locally optimum receiver implementation is explicitly determined. These structure are shown to provide considerable improvement over conventional linear receiver structures. The basis of comparison is taken as the asymptotic relative efficiency (ARE). Unfortunately, the locally optimum receiver requires explicit a priori knowledge of the underlying noise distribution. To circumvent this difficulty a rather simple adaptive nonlinear receiver structure is described which attempts to adapt to the unknown prevailing noise environment.
AB - A class of nonlinear receiver structures is described for the detection of weak signals in non-Gaussian narrowband noise. In particular, the concept of a locally optimum receiver structure is extended to the case of narrowband signal and noise models. A useful class of non-Gaussian narrowband signal and noise models. A useful class of non-Gaussian narrowband noise models is developed for which the locally optimum receiver implementation is explicitly determined. These structure are shown to provide considerable improvement over conventional linear receiver structures. The basis of comparison is taken as the asymptotic relative efficiency (ARE). Unfortunately, the locally optimum receiver requires explicit a priori knowledge of the underlying noise distribution. To circumvent this difficulty a rather simple adaptive nonlinear receiver structure is described which attempts to adapt to the unknown prevailing noise environment.
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UR - http://www.scopus.com/inward/citedby.url?scp=0018523304&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:0018523304
VL - IT-25
SP - 592
EP - 600
JO - IEEE Transactions on Information Theory
JF - IEEE Transactions on Information Theory
SN - 0018-9448
IS - 5
ER -