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Volumn , Issue , 2008, Pages

Detection of known targets in weibull clutter based on neural networks. Robustness study against target parameters changes

Author keywords

Neural networks; Radar detection; Weibull clutter

Indexed keywords

CLUTTER (INFORMATION THEORY); DETECTORS; PATTERN RECOGNITION SYSTEMS; SEAWATER; TARGETS; TRACKING RADAR;

EID: 61849185697     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/RADAR.2008.4721037     Document Type: Conference Paper
Times cited : (6)

References (17)
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    • Andina, D.1    Sanz-Gonzalez, J.L.2
  • 13
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    • Modelling and Simulation of Coherent Weibull Clutter
    • G. Li and K.B. Yu, "Modelling and Simulation of Coherent Weibull Clutter", in IEE Proc. Radar and Signal Processing, vol. 136, no. 1, pp. 2-12, 1989.
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    • Li, G.1    Yu, K.B.2
  • 14
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    • Training Feedforward Networks with Marquardt Algorithm
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    • Improving the Learning Speed of 2-layer Neural Networks by Choosing Initial Values of the Adaptive Weights
    • D. Nguyen and B. Widrow, "Improving the Learning Speed of 2-layer Neural Networks by Choosing Initial Values of the Adaptive Weights", in Proc. of the Int. Joint Conf. on Neural Networks, pp. 21-26, 1999.
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    • Robustness of the Likelihood Ratio Detector for Moderately Fluctuating Radar Targets
    • A. Di Vito and M. Nakli, "Robustness of the Likelihood Ratio Detector for Moderately Fluctuating Radar Targets", in IEE Proc. Radar. Sonar and Navigation, vol. 146, no. 2, pp. 107-112, 1999.
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    • Di Vito, A.1    Nakli, M.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.