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Volumn 38, Issue 8, 2011, Pages 10547-10553

Feature Selection and Neural Network for analysis of microstructural changes in magnetic materials

Author keywords

Envelope; Feature selection; Neural Networks; Nondestructive methods; Probabilistic Neural Networks

Indexed keywords

CLASSIFICATION RATES; ENVELOPE; FEATURE SELECTION; FEATURE SELECTION ALGORITHM; MICROSTRUCTURAL CHANGES; MICROSTRUCTURAL PARAMETERS; NONDESTRUCTIVE METHODS; PROBABILISTIC NEURAL NETWORKS;

EID: 79953697665     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2011.02.088     Document Type: Article
Times cited : (24)

References (25)
  • 1
    • 0344835882 scopus 로고    scopus 로고
    • Constructive training of probabilistic neural networks
    • DOI 10.1016/S0925-2312(97)00063-5, PII S0925231297000635
    • M.R. Berthold, and J. Diamond Constructive training of probabilistic neural networks NeuroComputing 19 1998 167 183 (Pubitemid 28210179)
    • (1998) Neurocomputing , vol.19 , Issue.1-3 , pp. 167-183
    • Berthold, M.R.1    Diamond, J.2
  • 3
    • 33845187182 scopus 로고    scopus 로고
    • Analysis of the stress dependent magnetic easy axis in ASTM 36 steel by the magnetic Barkhausen noise
    • DOI 10.1016/j.ndteint.2006.09.003, PII S0963869506000892
    • J. Capo-Sánchez, J.A. Perez-Benitez, and L.R. Padovese Analysis of the stress dependent magnetic easy axis in ASTM 36 steel by the magnetic Barkhausen noise NDT & E International 40 2007 168 172 (Pubitemid 44856273)
    • (2007) NDT and E International , vol.40 , Issue.2 , pp. 168-172
    • Capo-Sanchez, J.1    Perez-Benitez, J.2    Padovese, L.R.3
  • 5
    • 0031142667 scopus 로고    scopus 로고
    • An iterative pruning algorithm for feedforward neural networks
    • PII S1045922797017554
    • G. Castellano, A.M. Fanelli, and M. Pelillo A iterative pruning algorithm for feedforward neural IEEE Transactions on Neural Networks 8 3 1997 519 531 (Pubitemid 127767797)
    • (1997) IEEE Transactions on Neural Networks , vol.8 , Issue.3 , pp. 519-531
    • Castellano, G.1    Fanelli, A.M.2    Pelillo, M.3
  • 7
    • 4544320095 scopus 로고    scopus 로고
    • Feature selection in the independent component subspace for face recognition
    • H.K. Ekenel, and B. Sankur Feature selection in the independent component subspace for face recognition Pattern Recognition Letters 25 2004 1377 1388
    • (2004) Pattern Recognition Letters , vol.25 , pp. 1377-1388
    • Ekenel, H.K.1    Sankur, B.2
  • 8
    • 0029772586 scopus 로고    scopus 로고
    • Nondestructive evaluation of material parameters using neural networks
    • U. Fiedler, M. Kroning, and W.A. Theiner Nondestructive evaluation of material parameters using neural networks Materials Science Forum 210-213 1 1996 343 348 (Pubitemid 126542451)
    • (1996) Materials Science Forum , vol.210-213 , Issue.PART 1 , pp. 343-348
    • Fiedler, U.1    Kroning, M.2    Theiner, W.A.3
  • 9
    • 0000783575 scopus 로고
    • The upstart: A method for constructing and training feedfoward neural networks
    • M. Frean The upstart: A method for constructing and training feedfoward neural networks Neural Computation 2 2 1990 198 209
    • (1990) Neural Computation , vol.2 , Issue.2 , pp. 198-209
    • Frean, M.1
  • 11
    • 56549094735 scopus 로고    scopus 로고
    • Enhanced feature selection models using gradient-based and point injection techniques
    • D. Huang, Z. Gan, and T.W.S. Chow Enhanced feature selection models using gradient-based and point injection techniques Neurocomputing 71 2008 3114 3123
    • (2008) Neurocomputing , vol.71 , pp. 3114-3123
    • Huang, D.1    Gan, Z.2    Chow, T.W.S.3
  • 12
    • 0030124529 scopus 로고    scopus 로고
    • Neural network classification of flaws detected by ultrasonic means
    • DOI 10.1016/0963-8695(95)00053-4
    • A. Masnata, and M. Sunseri Neural network classification of flaws detected by ultrasonic means NDT & E International 29 2 1996 87 93 (Pubitemid 126375691)
    • (1996) NDT and E International , vol.29 , Issue.2 , pp. 87-93
    • Masnata, A.1    Sunseri, M.2
  • 14
    • 67349133167 scopus 로고    scopus 로고
    • An improvement on floating search algorithms for feature subset selection
    • S. Nakariyakul, and D.P. Casasent An improvement on floating search algorithms for feature subset selection Pattern Recognition 42 2009 1932 1940
    • (2009) Pattern Recognition , vol.42 , pp. 1932-1940
    • Nakariyakul, S.1    Casasent, D.P.2
  • 16
    • 13544257113 scopus 로고    scopus 로고
    • A model for the influence of microstructural defects on magnetic Barkhausen noise in plain steels
    • DOI 10.1016/j.jmmm.2004.09.134, PII S0304885304010741
    • J.A. Perez-Benitez, J. Capo-Sánchez, J. Anglada-Rivera, and L.R. Padovese A model for the influence of microstructural defects on magnetic Barkhausen noise in plain steels Journal of Magnetism and Magnetic Materials 288 2005 433 442 (Pubitemid 40220129)
    • (2005) Journal of Magnetism and Magnetic Materials , vol.288 , pp. 433-442
    • Perez-Benitez, J.A.1    Capo-Sanchez, J.2    Anglada-Rivera, J.3    Padovese, L.R.4
  • 18
    • 10744229082 scopus 로고    scopus 로고
    • Dependence of the magnetic Barkhausen emission with carbon content in commercial steels
    • J.A. Perez-Benitez, L.R. Padovese, and J. Capo-Sánchez Dependence of the magnetic Barkhausen emission with carbon content in commercial steels Journal of Materials Science 39 2004 1367 1370
    • (2004) Journal of Materials Science , vol.39 , pp. 1367-1370
    • Perez-Benitez, J.A.1    Padovese, L.R.2    Capo-Sánchez, J.3
  • 19
    • 60949108366 scopus 로고    scopus 로고
    • Comparative study between traditional and modified probabilistic neural networks
    • S. Ramakrishnan, and M.M. Ibrahiem Comparative study between traditional and modified probabilistic neural networks Telecommunication Systems 40 2009 67 74
    • (2009) Telecommunication Systems , vol.40 , pp. 67-74
    • Ramakrishnan, S.1    Ibrahiem, M.M.2
  • 21
    • 0033220764 scopus 로고    scopus 로고
    • Adaptive floating search methods in feature selection
    • DOI 10.1016/S0167-8655(99)00083-5
    • P. Somol, P. Pudil, J. Novovicová, and P. Paclík Adaptive floating search methods in feature selection Pattern Recognition Letters 20 1999 1157 1163 (Pubitemid 32261893)
    • (1999) Pattern Recognition Letters , vol.20 , Issue.11-13 , pp. 1157-1163
    • Somol, P.1    Pudil, P.2    Novovicova, J.3    Paclik, P.4
  • 22
    • 78650731263 scopus 로고    scopus 로고
    • Feature selection from Barkhausen noise data using genetic algorithms with cross-validation
    • Springer Berlin/Heidelberg
    • A. Sorsa, and K. Leiviskä Feature selection from Barkhausen noise data using genetic algorithms with cross-validation Adaptive and natural computing algorithms 2009 Springer Berlin/Heidelberg (pp. 213-222)
    • (2009) Adaptive and Natural Computing Algorithms
    • Sorsa, A.1    Leiviskä, K.2
  • 23
    • 0025399335 scopus 로고
    • Probabilistic neural networks and the polynomial adaline as complementary techniques for classification
    • D.F. Specht Probabilistic neural networks and the polynomial adaline as complementary techniques for classification IEEE Transactions on Neural Networks 1 1 1990 111 121
    • (1990) IEEE Transactions on Neural Networks , vol.1 , Issue.1 , pp. 111-121
    • Specht, D.F.1
  • 24
    • 1642632805 scopus 로고    scopus 로고
    • Non-linear filtering of ultrasonic signals using neural networks
    • R. Vicen, R. Gil, and P. Jarabo Non-linear filtering of ultrasonic signals using neural networks Ultrasonics 42 1-9 2004 355 360
    • (2004) Ultrasonics , vol.42 , Issue.19 , pp. 355-360
    • Vicen, R.1    Gil, R.2    Jarabo, P.3
  • 25
    • 0032124116 scopus 로고    scopus 로고
    • Introduction to the modified probabilistic neural network
    • - [2] Perez-Benitez JA
    • A. Zaknich Introduction to the modified probabilistic neural network IEEE Transactions on Signal Processing 46 7 1998 1980 1990
    • (1998) IEEE Transactions on Signal Processing , vol.46 , Issue.7 , pp. 1980-1990
    • Zaknich, A.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.