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Signal Detection in Correlated Non-Gaussian Noise Using Higher-Order Statistics
- Source :
- Circuits, Systems, and Signal Processing. 37:1704-1723
- Publication Year :
- 2017
- Publisher :
- Springer Science and Business Media LLC, 2017.
-
Abstract
- The authors of this paper study the synthesis of new models and methods for signal detection in additive correlated non-Gaussian noise. A new moment quality criterion decision making is proposed based on a random process description using moments and a formation of polynomial decision rules. Taking into account parameters of non-Gaussian distribution of random variables (such as the moments of third and higher orders and joint cumulants), it is shown that nonlinear processing of samples can increase the signal processing efficiency. A synthesis of effective methods and algorithms of data processing in non-Gaussian noise is also presented in this work.
- Subjects :
- Noise measurement
Noise (signal processing)
Applied Mathematics
020206 networking & telecommunications
Higher-order statistics
02 engineering and technology
White noise
Gaussian random field
Moment (mathematics)
symbols.namesake
Additive white Gaussian noise
Gaussian noise
Signal Processing
Statistics
0202 electrical engineering, electronic engineering, information engineering
symbols
020201 artificial intelligence & image processing
Algorithm
Mathematics
Subjects
Details
- ISSN :
- 15315878 and 0278081X
- Volume :
- 37
- Database :
- OpenAIRE
- Journal :
- Circuits, Systems, and Signal Processing
- Accession number :
- edsair.doi...........8968a29ecaf25ca693517454ad880407