Bibliografia
115
Bibliografia
[1] V.N. Vapnik. “The nature of statistical learning theory” New York, Springer-Verlag,1995.
[2] S. Haykin. “Neural Networks-a comprehensive foundation”. Pearson Education,1999.
[3] S. Theodoridis, K. Koutroumbas “Pattern Recognition” Elsevier, 2003.
[4] J.C. Burges. “A tutorial on Support Vector Machines for Pattern Recognition”. Data Mining and Knowledge Discovery 2, 121-167, 1998.
[5] Li Ying, Ren Yong, Shan Xiuming. “Radar HRRP Classification with Support Vector Machines” .IEEE Proceedings Info-tech and Info-net. 2001, 218-226.
[6] Wang Xiao-dan, Wang Ji-qin. “Support Vector Machines for HRRP Classification.IEEE”
Proceedings on Signal processing and its application. 2003, 337-340.
[7] Xiao-Dan Wang, Chong-Ming Wu. “Using improved SVM decision tree to classify HRRP”. IEEE Proceedings on Machine learning and Cybernetics. 2005,4432-4436.
[8] Xiao Huaitie, Guo Lei, Fu Qiang. “Radar Target Recognition method using Improved Support Vector Machines based on Polarized HRRP”. Proceedings on Computational Inteligence and Security. 2006, 702-707.
[9] S.R Cloude, “Uniquess of Target Decomposition Theorem in Radar Polarimetry” direct and inverse methods in radar polarimetry, NATO ASI series, vol. 1,pp 267-296,1992.
[10] Jeng-Kuang Hwang, Kun-Yo Lin, Yu-Lun Chiu,and Juinn_Horng Deng. “Automatic Target Recognition based on High Resolution Range Profiles with Unknown Circular Range Shift”. IEEE International Symposium on Signal Processing and Information Technology2006.
[11] R. Soleti, L.Cantini, F. Berizzi, A.Capria, D. Calugi. “Neural Networks for Polarimetric Radar Target Classification”. Proc. USIPCO 2006 Florence Italy.
Bibliografia
116 [12] R.A Mitchell, J Westerkamp. “Robust Statistical Fetaure Based Aircraft Identification”.
IEEE Transaction on Aerospace Electronics Systems, 1999.
[13] F. Berizzi, M. Martorella, A. Capria, R. Paladini. “H/α Polarimetric Features for Man Made Target Classification”. Proc. IEEE RADARCONF 08, Roma, May 2008.
[14] S.R. Cloude, E. Pottier. “An Entropy Based Classification Scheme for Polarimetric SAR”. IEEE Transaction on Geoscience and Remote Sensing. Vol. 35 n°1, January 2007.
[15] D.Giuli “Polarization Diversity in Radar” Proc. The IEE 1986.
[16] G. Galati, F. Mazzenga, M. Naldi. “Elementi di sistemi radar”. Aracne 1996.
[17] M. Skolnik. “Radar Handbook”. McGraw-Hill 1990.
[18] M. Novak, J.Owirka, S.Browser, L. Weaver. “The Automatic Target Recognition System in SAIP”. The Lincoln Laboratoatory Journal, Vol. 10 n° 2, 1997.
[19] F. Sadjadi. “Improved Target Classification Using Optimum Polarimetric SAR signatures”. IEEE Transaction on Aerospace and Electronic Systems. January 2002.
[20] Jeng Kuang Hwang, Kun-Yo Lin, Yu-Lun Chiu. “Automatic Target Recognition based on High Resolution Range Profile with Unknown Circular Range Shifth”. Symposium on Signal Processing and Information Technology. 2006.
[21] Qun Zhao, C. Principe. “Support Vector Machines for SAR Automatic Target Recognition”, IEEE Transaction on Aerospace and Electronic Systems. Vol. 37 n° 2, April 2001.
[22] S.P Jacobs, J. O’Sullivan. “Automatic Target Recognition Using Sequence of High Resolution Radar Range Profiles”. IEEE Transaction on Aerospace and Electronic Systems 2000.
Bibliografia
117 [23] E. Ertin, L.C. Potter. “Polarimetric Classification of Scattering Centers Using M-ary Bayesian decision Rules”. IEEE Transaction on Aerospace and Electronic Systems. July 2000.
[24] Kuo Chu Chang, Yi Chuan Lu. “High Resolution Polarimetric SAR Target Classification with Neural Networks”. IEEE 1995.
[25] M.T. Hagan, M.B. Menhaj, "Training feedforward networks with the Marquardt algorithm,'' IEEE Transactions on Neural Networks, vol. 5, no. 6, pp. 989–993, November 1994.
[26] C.Daqing, B. Zheng, “High range radar Target Identification Using Multilayer Feedforward Neural Network, 1996 CIE Radar Coneference, Oct.1996, vol2, pp.215-218.
[27] Z.Xun, S. Ronghui, G, Guirong, “Automatic HRR target recognittion based on Prony model, Wavelet and Probability Neural Network” Radar, 1996 CIE International Conference of radar, 8-10 Oct. 1996 pp. 143-146.
[28] C.T.Chen, K.S. Chen, J.S. Lee, “The use of Fully polarimetric Information for the Fuzzy Neural classification of SAR images, “Tr on GRS, Vol.41, No.9, Sept, 2003, pp. 2089-2100.
[29] M.A. khabou, P.D. Gader, “Automatic target detection using entropy optimized Share- Weight Neural Network”, Tr.on Neural Networks, Vol.11, No.1m Jan, 2000, pp.186-193.
[30] L. Devroye, L. Gyorfi, G. Lugosi “A probabilistic Theory of Pattern Recognition, Springer-Verlag 1996.
[31] R. Duda, P. Hart “Pattern Clòassification and Scene Analysis, John Wiley, 1973.
[32] J.P. Marques”Pattern Recognition” Springer Verlag, 2001.
Bibliografia
118 [33] B.Bhanu, Y.Lin, K. Krawiec “Evolutionary Syntesis of Pattern Recognition Systems”, Springer Verlag, 2005.
[34] P.R. Runkle, P.K. Bharadwaj, L. Couchman, L. Carin, “Hidden Markow Models for Multiaspect Target Identification”, IEEE Trans. On Signal Processin, vol. 47 n°7, pp. 2035- 2040, July 1999.
[35] N. F. Chanberlain, “Syntactic Classification of Radar Target using Polarimetric Signatures” System Engineering, 1990, IEEE international conference, pp. 490-494.
[36] F.Berizzi, M.Martorella, A. Cacciamano. “Synthetic Range Profile Focusing via Contrast Optimization” Proc. Igarss Barcellona 2007.