Birleşik sezim ve kestirim sistemlerinin gürültü ile geliştirilmesi
Author
Akbay, Abdullah Başar
Gezici, Sinan
Date
2014-04Source Title
22nd Signal Processing and Communications Applications Conference, SIU 2014 - Proceedings
Publisher
IEEE
Pages
1059 - 1062
Language
Turkish
Type
Conference PaperItem Usage Stats
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Abstract
Belirli koşullar altında, optimal olmayan bazı sezici ve kestiricilerin performansını girdilerine gürültü ekleyerek geliştirmek mümkündür. Bu çalışmada, birleşik bir sezim ve kestirim sisteminin gürültü eklenerek geliştirilmesi incelenmektedir. Sistem performansının maksimizasyonu bir optimizasyon problemi olarak tanımlanmaktadır. Optimal toplanır gürültü dağılımının istatiksel özellikleri belirlenmektedir. Sistem performansının gürültü ile iyileştirilemeyeceği bir koşul elde edilmektedir.Önerilen optimizasyon probleminin, bir doğrusal programlama (DP) problemi olarak yaklaşımı sunulmaktadır. Bir sayısal örnek üzerinde, kuramsal bulguları desteklemek amacıyla, gürültü eklenmiş sistem ile orijinal sistemin performansları karşılaştırılmaktadır. Adding noise to inputs of some suboptimal detectors or estimators can improve their performance under certain conditions. In this study, a noise enhanced joint detection and estimation system is investigated. Maximization of the system performance is defined as an optimization problem. Statistical characterization of the optimal additive noise distribution is determined. A condition under which performance of the system cannot be improved is obtained. The proposed optimization problem is approximated as a linear programming (LP) problem. With an illustrative numerical example, a performance comparison between the noise enhanced system and the original system is performed to support the theoretical analysis. © 2014 IEEE.
Keywords
DetectionEstimation
Linear programming
Noise enhanced detection and estimation
Error detection
Estimation
Linear programming
Numerical methods
Signal processing
Joint detection
Noise distribution
Noise enhancement
Noise-enhanced detection
Optimization problems
Original systems
Performance comparison
Statistical characterization
Optimization
Permalink
http://hdl.handle.net/11693/27853Published Version (Please cite this version)
http://dx.doi.org/10.1109/SIU.2014.6830415Collections
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