Incremental learning approach based on vector neural network for emitter identification

IET Signal Processing

Volumn 4, Issue 1, 2010, Pages 45-54

  Liu, H J ^a   Liu, Z ^a   Jiang, W L ^a   Zhou, Y Y ^a  

^a NATIONAL UNIVERSITY OF DEFENSE TECHNOLOGY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATIC UPDATING; EMITTER IDENTIFICATION; FEATURE PARAMETERS; INCREMENTAL LEARNING; MEASUREMENT UNCERTAINTY; NONLINEAR MAPPINGS; VECTOR NEURAL NETWORKS; WEAK CLASSIFIERS;

ALGORITHMS; NEURAL NETWORKS; UNCERTAINTY ANALYSIS;

IDENTIFICATION (CONTROL SYSTEMS);

EID: 84860864479     PISSN: 17519675     EISSN: 17519683     Source Type: Journal    
DOI: 10.1049/iet-spr.2008.0240     Document Type: Article

References (20)

1. SCHLEHER D.C.: 'Introduction to electronic warfare' (Artech House, New York, 1986)
2. LIU J., LEE J.P.Y., LI L., LUO Z.-Q., WONG K.M.: 'Online clustering algorithms for radar emitter classification', IEEE Trans. Pattern Anal. Mach. Intell., 2005, 27, (8), pp. 1185-1196
3. WNUK M., KAWALEC A., DUDCZYK J., OWCZAREK R.: 'The method of regression analysis approach to the specific emitter identification'. Proc. 16th Int. Conf. Microwaves, Radar and Wireless Communications (MIKON 2006), Krakow, Poland, May 2006, pp. 491-494
4. MATUSZEWSKI J.: 'Specific emitter identification'. Proc. Int. Radar Symp. (IRS 2008), Wroclaw, Poland, May 2008, pp. 1-4
5. XU D., YANG B., JIANG W.L., ZHOU Y.Y.:'An improved SVDUIKPCA algorithm for specific emitter identification'. Proc. IEEE Int. Conf. Information and Automation (ICIA 2008), Zhangjiajie, China, June 2008, pp. 692-696
6. LIU M.-W., DOHERTY J.F.: 'Specific emitter identification using nonlinear device estimation'. Proc. IEEE Sarnoff Symp. (SARNOFF 2008), Princeton, NJ, USA, April 2008, pp. 1-5
7. HUO Q., LEE C.-H.: 'A Bayesian predictive classification approach to robust speech recognition', IEEE Trans. Speech Audio Process., 2000, 8, (2), pp. 200-204
8. HASSAN S.A., BHATTI A.I., LATIF A.: 'Emitter recognition using fuzzy inference system'. Proc. IEEE Int. Symp. Emerging Technologies, Islamabad, Pakistan, September 2005, pp. 204-208
9. ZHANG B., SRIHARI S.N.: 'Fast k-nearest neighbor classification using cluster-based trees', IEEE Trans. Pattern Anal. Mach. Intell., 2004, 26, (4), pp. 525-528
10. WILLSON G.B.: 'Radar classification using a neural network', Proc. Appl. Artif. Neural Netw., SPIE, 1990, 1294, pp. 200-210
11. ISHIBUCHI H., FUJIOKA R., TANAKA H.: 'Neural networks that learn from fuzzy if-then rules', IEEE Trans. Fuzzy Syst., 1993, 1, (2), pp. 85-97
12. ISHIBUCHI H., YAMAMOTO T.: 'Rule weight specification in fuzzy rule-based classification systems', IEEE Trans. Fuzzy Syst., 2005, 13, (4), pp. 428-435
13. SHIEH C.-S., LIN C.-T.: 'A vector neural network for emitter identification', IEEE Trans. Antennas Propag., 2002, 50, (8), pp. 1120-1127
14. FU L.: 'Incremental knowledge acquisition in supervised learning networks', IEEE Trans. Syst. Man Cybern., 1996, 26, (6), pp. 801-809
15. WAN S., BANTA L.E.: 'Parameter incremental learning algorithm for neural networks', IEEE Trans. Neural Netw., 2006, 17, (6), pp. 1424-1438
16. KIDERA T., OZAWA S., ABE S.: 'An incremental learning algorithm of ensemble classifier systems'. Int. Joint Conf. Neural Networks (IJCNN 2006), Vancouver, BC, Canada, July 2006, pp. 3421-3427
17. POLIKAR R., UPDA L., UPDA S.S., HONAVAR V.:'Learn++:an incremental learning algorithm for supervised neuralnetworks', IEEE Trans. Syst. Man Cybern., 2001, 31,(4), pp. 497-508
18. PARIKH D., POLIKAR R.: 'An ensemble-based incremental learning approach to data fusion', IEEE Trans. Syst. Man Cybern., 2007, 37, (2), pp. 437-450
19. http://en.wikipedia.org/wiki/Iris_flower_data_set, accessed April 2008
20. LIAO S.S., TANG T.H., LIU W.-Y.: 'Finding relevant sequences in time series containing crisp, interval, and fuzzy interval data', IEEE Trans. Syst. Man Cybern., 2004, 34, (5), pp. 2071-2079