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Volumn 17, Issue 3, 2013, Pages 519-533

Generalised Gaussian radial basis function neural networks

Author keywords

Classification; Evolutionary algorithm; Generalised radial basis function; Neural networks

Indexed keywords

CLASSIFICATION (OF INFORMATION); EVOLUTIONARY ALGORITHMS; FUNCTIONS; GAUSSIAN DISTRIBUTION; HEAT CONDUCTION; IMAGE SEGMENTATION; INVERSE PROBLEMS; LOGISTIC REGRESSION; NEURAL NETWORKS; RADIAL BASIS FUNCTION NETWORKS; SUPPORT VECTOR MACHINES; SUPPORT VECTOR REGRESSION;

EID: 84873751200     PISSN: 14327643     EISSN: 14337479     Source Type: Journal    
DOI: 10.1007/s00500-012-0923-4     Document Type: Article
Times cited : (18)

References (41)
  • 2
    • 80051670016 scopus 로고    scopus 로고
    • The use of coevolution and the artificial immune system for ensemble learning
    • Barbosa BHG, Bui LT, Abbass HA, Aguirre LA, Braga AP (2011) The use of coevolution and the artificial immune system for ensemble learning. Softw Comput 15(9): 1735-1747.
    • (2011) Softw Comput , vol.15 , Issue.9 , pp. 1735-1747
    • Barbosa, B.H.G.1    Bui, L.T.2    Abbass, H.A.3    Aguirre, L.A.4    Braga, A.P.5
  • 3
    • 33750381252 scopus 로고    scopus 로고
    • Image thresholding based on the em algorithm and the generalized Gaussian distribution
    • Bazi Y, Bruzzone L, Melgani F (2007) Image thresholding based on the em algorithm and the generalized gaussian distribution. Pattern Recognit 40(2): 619-634.
    • (2007) Pattern Recognit , vol.40 , Issue.2 , pp. 619-634
    • Bazi, Y.1    Bruzzone, L.2    Melgani, F.3
  • 6
    • 0036505590 scopus 로고    scopus 로고
    • Unsupervised clustering with spiking neurons by sparse temporal coding and multi-layer RBF networks
    • Bohte SM, La Poutr H, Kok JN (2002) Unsupervised clustering with spiking neurons by sparse temporal coding and multi-layer rbf networks. IEEE Trans Neural Netw 13(2): 426-435.
    • (2002) IEEE Trans Neural Netw , vol.13 , Issue.2 , pp. 426-435
    • Bohte, S.M.1    la Poutr, H.2    Kok, J.N.3
  • 8
    • 67649380729 scopus 로고    scopus 로고
    • Probabilistic classification vector machines
    • Chen H, Tino P, Yao X (2009) Probabilistic classification vector machines. IEEE Trans Neural Netw 20(6): 901-914.
    • (2009) IEEE Trans Neural Netw , vol.20 , Issue.6 , pp. 901-914
    • Chen, H.1    Tino, P.2    Yao, X.3
  • 9
    • 84859435856 scopus 로고    scopus 로고
    • A multi-objective neural network based method for cover crop identification from remote sensed data
    • Cruz-Ramírez M, Hervás-Martínez C, Jurado-Expósito M, López-Granados F (2012) A multi-objective neural network based method for cover crop identification from remote sensed data. Expert Syst Appl 39(11): 10, 038-10, 048.
    • (2012) Expert Syst Appl , vol.39 , Issue.11 , pp. 038-048
    • Cruz-Ramírez, M.1    Hervás-Martínez, C.2    Jurado-Expósito, M.3    López-Granados, F.4
  • 10
    • 29644438050 scopus 로고    scopus 로고
    • Statistical comparisons of classifiers over multiple data sets
    • Demsar J (2006) Statistical comparisons of classifiers over multiple data sets. J Mach Learn Res 7: 1-30.
    • (2006) J Mach Learn Res , vol.7 , pp. 1-30
    • Demsar, J.1
  • 11
    • 0036474679 scopus 로고    scopus 로고
    • Wavelet-based texture retrieval using generalized Gaussian density and Kullback-Leibler distance
    • Do MN, Vetterli M (2002) Wavelet-based texture retrieval using generalized Gaussian density and Kullback-Leibler distance. IEEE Trans Image Process 11(2): 146-158.
    • (2002) IEEE Trans Image Process , vol.11 , Issue.2 , pp. 146-158
    • Do, M.N.1    Vetterli, M.2
  • 13
    • 0001837148 scopus 로고
    • A comparison of alternative tests of significance for the problem of m rankings
    • Friedman M (1940) A comparison of alternative tests of significance for the problem of m rankings. Ann Math Stat 11(1): 86-92.
    • (1940) Ann Math Stat , vol.11 , Issue.1 , pp. 86-92
    • Friedman, M.1
  • 14
    • 70349275214 scopus 로고    scopus 로고
    • Image category learning and classification via optimal linear combination of multiple partially matching kernels
    • Fu S, Yang G, Hou Z (2010) Image category learning and classification via optimal linear combination of multiple partially matching kernels. Softw Comput 14(2): 181-192.
    • (2010) Softw Comput , vol.14 , Issue.2 , pp. 181-192
    • Fu, S.1    Yang, G.2    Hou, Z.3
  • 15
    • 0037983742 scopus 로고    scopus 로고
    • Data dimensionality reduction with application to simplifying rbf network structure and improving classification performance
    • Fu X, Wang L (2003) Data dimensionality reduction with application to simplifying rbf network structure and improving classification performance. IEEE Trans Syst Man Cybern Part B Cybern 33(3): 399-409.
    • (2003) IEEE Trans Syst Man Cybern Part B Cybern , vol.33 , Issue.3 , pp. 399-409
    • Fu, X.1    Wang, L.2
  • 16
    • 39749144459 scopus 로고    scopus 로고
    • Random weighting estimation of parameters in generalized Gaussian distribution
    • Gao S, Feng Z, Zhong Y, Shirinzadeh B (2008) Random weighting estimation of parameters in generalized Gaussian distribution. Inf Sci 178(9): 2275-2281.
    • (2008) Inf Sci , vol.178 , Issue.9 , pp. 2275-2281
    • Gao, S.1    Feng, Z.2    Zhong, Y.3    Shirinzadeh, B.4
  • 17
    • 58149287952 scopus 로고    scopus 로고
    • An extension on "statistical comparisons of classifiers over multiple data sets" for all pairwise comparisons
    • García S, Herrera F (2008) An extension on "statistical comparisons of classifiers over multiple data sets" for all pairwise comparisons. J Mach Learn Res 9: 2677-2694.
    • (2008) J Mach Learn Res , vol.9 , pp. 2677-2694
    • García, S.1    Herrera, F.2
  • 19
    • 77952880576 scopus 로고    scopus 로고
    • Designing multilayer perceptrons using a guided saw-tooth evolutionary programming algorithm
    • Gutiérrez PA, Hervás C, Lozano M (2010) Designing multilayer perceptrons using a guided saw-tooth evolutionary programming algorithm. Softw Comput 14(6): 599-613.
    • (2010) Softw Comput , vol.14 , Issue.6 , pp. 599-613
    • Gutiérrez, P.A.1    Hervás, C.2    Lozano, M.3
  • 20
    • 0001683814 scopus 로고
    • Layered neural networks with Gaussian hidden units as universal approximations
    • Hartman EJ, Keeler JD, Kowalski JM (1990) Layered neural networks with Gaussian hidden units as universal approximations. Neural Comput 2(2): 210-215.
    • (1990) Neural Comput , vol.2 , Issue.2 , pp. 210-215
    • Hartman, E.J.1    Keeler, J.D.2    Kowalski, J.M.3
  • 22
    • 51049123604 scopus 로고    scopus 로고
    • Multilogistic regression by means of evolutionary product-unit neural networks
    • Hervs-Martnez C, Martnez-Estudillo FJ, Carbonero-Ruz M (2008) Multilogistic regression by means of evolutionary product-unit neural networks. Neural Netw 21(7): 951-961.
    • (2008) Neural Netw , vol.21 , Issue.7 , pp. 951-961
    • Hervs-Martnez, C.1    Martnez-Estudillo, F.J.2    Carbonero-Ruz, M.3
  • 24
    • 0037238922 scopus 로고    scopus 로고
    • Empirical evaluation of the improved rprop learning algorithms
    • Igel C, Hsken M (2003) Empirical evaluation of the improved rprop learning algorithms. Neurocomputing 50(6): 105-123.
    • (2003) Neurocomputing , vol.50 , Issue.6 , pp. 105-123
    • Igel, C.1    Hsken, M.2
  • 25
    • 21744441138 scopus 로고    scopus 로고
    • Exponent parameter estimation for generalized Gaussian probability density functions with application to speech modeling
    • Kokkinakis K, Nandi AK (2005) Exponent parameter estimation for generalized Gaussian probability density functions with application to speech modeling. Signal Process 85(9): 1852-1858.
    • (2005) Signal Process , vol.85 , Issue.9 , pp. 1852-1858
    • Kokkinakis, K.1    Nandi, A.K.2
  • 27
    • 28244473101 scopus 로고    scopus 로고
    • Approximated fast estimator for the shape parameter of generalized gaussian distribution
    • Krupinski R, Purczynski J (2006) Approximated fast estimator for the shape parameter of generalized gaussian distribution. Signal Process 86(2): 205-211.
    • (2006) Signal Process , vol.86 , Issue.2 , pp. 205-211
    • Krupinski, R.1    Purczynski, J.2
  • 28
    • 60249094201 scopus 로고    scopus 로고
    • A study on the use of statistical tests for experimentation with neural networks: Analysis of parametric test conditions and non-parametric tests
    • Luengo J, García S, Herrera F (2009) A study on the use of statistical tests for experimentation with neural networks: Analysis of parametric test conditions and non-parametric tests. Expert Syst Appl 36(4): 7798-7808.
    • (2009) Expert Syst Appl , vol.36 , Issue.4 , pp. 7798-7808
    • Luengo, J.1    García, S.2    Herrera, F.3
  • 29
    • 16544373696 scopus 로고    scopus 로고
    • Efficient training of rbf networks for classification
    • Nabney IT (2004) Efficient training of rbf networks for classification. Int J Neural Syst 14(3): 201-208.
    • (2004) Int J Neural Syst , vol.14 , Issue.3 , pp. 201-208
    • Nabney, I.T.1
  • 30
    • 33750991863 scopus 로고    scopus 로고
    • Localized generalization error of gaussian-based classifiers and visualization of decision boundaries
    • Ng WWY, Yeung DS, Wang D, Tsang ECC, Wang XZ (2007) Localized generalization error of gaussian-based classifiers and visualization of decision boundaries. Softw Comput 11(4): 375-381.
    • (2007) Softw Comput , vol.11 , Issue.4 , pp. 375-381
    • Ng, W.W.Y.1    Yeung, D.S.2    Wang, D.3    Tsang, E.C.C.4    Wang, X.Z.5
  • 32
    • 33847421698 scopus 로고    scopus 로고
    • A novel continuous forward algorithm for RBF neural modelling
    • Peng JX, Li K, Irwin G (2007) A novel continuous forward algorithm for RBF neural modelling. IEEE Trans Autom Control 52: 117-122.
    • (2007) IEEE Trans Autom Control , vol.52 , pp. 117-122
    • Peng, J.X.1    Li, K.2    Irwin, G.3
  • 33
    • 33747878901 scopus 로고    scopus 로고
    • Improve maximum likelihood estimation for subband GGD parameters
    • Pi M (2006) Improve maximum likelihood estimation for subband GGD parameters. Pattern Recognit Lett 27(14): 1710-1713.
    • (2006) Pattern Recognit Lett , vol.27 , Issue.14 , pp. 1710-1713
    • Pi, M.1
  • 34
    • 0032299256 scopus 로고    scopus 로고
    • The role of constraints within generalized nonextensive statistics
    • Tsallis C, Mendes RS, Plastino AR (1998) The role of constraints within generalized nonextensive statistics. Phys A: Stat Mech Appl 261(3-4): 534-554.
    • (1998) Phys A: Stat Mech Appl , vol.261 , Issue.3-4 , pp. 534-554
    • Tsallis, C.1    Mendes, R.S.2    Plastino, A.R.3
  • 35
    • 0001668641 scopus 로고
    • Parametric generalized Gaussian density estimation
    • Varanasi MK, Aazhang B (1989) Parametric generalized Gaussian density estimation. J Acoust Soc Am 86(4): 1404-1415.
    • (1989) J Acoust Soc Am , vol.86 , Issue.4 , pp. 1404-1415
    • Varanasi, M.K.1    Aazhang, B.2
  • 38
    • 0027057407 scopus 로고
    • Statistical comparisons of classifiers over multiple data sets
    • Wright S (1992) Statistical comparisons of classifiers over multiple data sets. Biometrics 48: 1005-1013.
    • (1992) Biometrics , vol.48 , pp. 1005-1013
    • Wright, S.1
  • 39
    • 55349089531 scopus 로고    scopus 로고
    • Sparse estimation automatically selects voxels relevant for the decoding of fmri activity patterns
    • Yamashita O, Sato M, Yoshioka T, Tong F, Kamitani Y (2008) Sparse estimation automatically selects voxels relevant for the decoding of fmri activity patterns. NeuroImage 42(4): 1414-1429.
    • (2008) NeuroImage , vol.42 , Issue.4 , pp. 1414-1429
    • Yamashita, O.1    Sato, M.2    Yoshioka, T.3    Tong, F.4    Kamitani, Y.5
  • 40
    • 0031143030 scopus 로고    scopus 로고
    • A new evolutionary system for evolving artificial neural networks
    • Yao X, Liu Y (1997) A new evolutionary system for evolving artificial neural networks. IEEE Trans Neural Netw 8(3): 694-713.
    • (1997) IEEE Trans Neural Netw , vol.8 , Issue.3 , pp. 694-713
    • Yao, X.1    Liu, Y.2
  • 41
    • 77957889304 scopus 로고    scopus 로고
    • Employing multiple-kernel support vector machines for counterfeit banknote recognition
    • Yeh C, Su W, Lee S (2011) Employing multiple-kernel support vector machines for counterfeit banknote recognition. Appl Softw Comput J 11(1): 1439-1447.
    • (2011) Appl Softw Comput J , vol.11 , Issue.1 , pp. 1439-1447
    • Yeh, C.1    Su, W.2    Lee, S.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.