These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
300 related articles for article (PubMed ID: 19923045)
21. A generalized least absolute deviation method for parameter estimation of autoregressive signals. Xia Y; Kamel MS IEEE Trans Neural Netw; 2008 Jan; 19(1):107-18. PubMed ID: 18269942 [TBL] [Abstract][Full Text] [Related]
22. Bagging and boosting negatively correlated neural networks. Islam MM; Yao X; Shahriar Nirjon SM; Islam MA; Murase K IEEE Trans Syst Man Cybern B Cybern; 2008 Jun; 38(3):771-84. PubMed ID: 18558541 [TBL] [Abstract][Full Text] [Related]
23. Learning ensembles of neural networks by means of a Bayesian artificial immune system. Castro PA; Von Zuben FJ IEEE Trans Neural Netw; 2011 Feb; 22(2):304-16. PubMed ID: 21189236 [TBL] [Abstract][Full Text] [Related]
24. Random sampler M-estimator algorithm with sequential probability ratio test for robust function approximation via feed-forward neural networks. El-Melegy MT IEEE Trans Neural Netw Learn Syst; 2013 Jul; 24(7):1074-85. PubMed ID: 24808522 [TBL] [Abstract][Full Text] [Related]
29. Epileptic EEG classification based on extreme learning machine and nonlinear features. Yuan Q; Zhou W; Li S; Cai D Epilepsy Res; 2011 Sep; 96(1-2):29-38. PubMed ID: 21616643 [TBL] [Abstract][Full Text] [Related]
30. Gene selection in cancer classification using sparse logistic regression with Bayesian regularization. Cawley GC; Talbot NL Bioinformatics; 2006 Oct; 22(19):2348-55. PubMed ID: 16844704 [TBL] [Abstract][Full Text] [Related]
31. A comparison of Bayesian network learning algorithms from continuous data. Fu LD; Tsamardinos I AMIA Annu Symp Proc; 2005; 2005():960. PubMed ID: 16779247 [TBL] [Abstract][Full Text] [Related]
32. Constructing a fuzzy rule-based system using the ILFN network and Genetic Algorithm. Yen GG; Meesad P Int J Neural Syst; 2001 Oct; 11(5):427-43. PubMed ID: 11709810 [TBL] [Abstract][Full Text] [Related]
33. A comparative study of data sampling techniques for constructing neural network ensembles. Akhand MA; Islam MM; Murase K Int J Neural Syst; 2009 Apr; 19(2):67-89. PubMed ID: 19496204 [TBL] [Abstract][Full Text] [Related]
34. An STDP training algorithm for a spiking neural network with dynamic threshold neurons. Strain TJ; McDaid LJ; McGinnity TM; Maguire LP; Sayers HM Int J Neural Syst; 2010 Dec; 20(6):463-80. PubMed ID: 21117270 [TBL] [Abstract][Full Text] [Related]
35. Simultaneous training of negatively correlated neural networks in an ensemble. Liu Y; Yao X IEEE Trans Syst Man Cybern B Cybern; 1999; 29(6):716-25. PubMed ID: 18252352 [TBL] [Abstract][Full Text] [Related]
37. Study of a fast discriminative training algorithm for pattern recognition. Li Q; Juang BH IEEE Trans Neural Netw; 2006 Sep; 17(5):1212-21. PubMed ID: 17001982 [TBL] [Abstract][Full Text] [Related]
38. Robust sequential learning of feedforward neural networks in the presence of heavy-tailed noise. Vuković N; Miljković Z Neural Netw; 2015 Mar; 63():31-47. PubMed ID: 25436486 [TBL] [Abstract][Full Text] [Related]
39. Negative correlation ensemble learning for ordinal regression. Fernández-Navarro F; Gutiérrez PA; Hervás-Martínez C; Yao X IEEE Trans Neural Netw Learn Syst; 2013 Nov; 24(11):1836-49. PubMed ID: 24808616 [TBL] [Abstract][Full Text] [Related]
40. A growing and pruning sequential learning algorithm of hyper basis function neural network for function approximation. Vuković N; Miljković Z Neural Netw; 2013 Oct; 46():210-26. PubMed ID: 23811384 [TBL] [Abstract][Full Text] [Related] [Previous] [Next] [New Search]