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.
98 related articles for article (PubMed ID: 18276398)
1. Dynamic programming approach to optimal weight selection in multilayer neural networks. Saratchandran P IEEE Trans Neural Netw; 1991; 2(4):465-7. PubMed ID: 18276398 [TBL] [Abstract][Full Text] [Related]
2. A fast multilayer neural-network training algorithm based on the layer-by-layer optimizing procedures. Wang GJ; Chen CC IEEE Trans Neural Netw; 1996; 7(3):768-75. PubMed ID: 18263473 [TBL] [Abstract][Full Text] [Related]
3. Comments on ;Dynamic programming approach to optimal weight selection in multilayer neural networks' [with reply]. Pearlmutter BA; Sanatchandran P IEEE Trans Neural Netw; 1992; 3(6):1028-9. PubMed ID: 18276503 [TBL] [Abstract][Full Text] [Related]
4. The No-Prop algorithm: a new learning algorithm for multilayer neural networks. Widrow B; Greenblatt A; Kim Y; Park D Neural Netw; 2013 Jan; 37():182-8. PubMed ID: 23140797 [TBL] [Abstract][Full Text] [Related]
5. On the initialization and optimization of multilayer perceptrons. Weymaere N; Martens JP IEEE Trans Neural Netw; 1994; 5(5):738-51. PubMed ID: 18267848 [TBL] [Abstract][Full Text] [Related]
6. Optimization of neural networks using variable structure systems. Mohseni SA; Tan AH IEEE Trans Syst Man Cybern B Cybern; 2012 Dec; 42(6):1645-53. PubMed ID: 22665508 [TBL] [Abstract][Full Text] [Related]
7. Single-hidden-layer feed-forward quantum neural network based on Grover learning. Liu CY; Chen C; Chang CT; Shih LM Neural Netw; 2013 Sep; 45():144-50. PubMed ID: 23545155 [TBL] [Abstract][Full Text] [Related]
8. A simple method to derive bounds on the size and to train multilayer neural networks. Sartori MA; Antsaklis PJ IEEE Trans Neural Netw; 1991; 2(4):467-71. PubMed ID: 18276399 [TBL] [Abstract][Full Text] [Related]
9. A clinical decision support system using multilayer perceptron neural network to assess well being in diabetes. Narasingarao MR; Manda R; Sridhar GR; Madhu K; Rao AA J Assoc Physicians India; 2009 Feb; 57():127-33. PubMed ID: 19582980 [TBL] [Abstract][Full Text] [Related]
10. An improvement of extreme learning machine for compact single-hidden-layer feedforward neural networks. Huynh HT; Won Y; Kim JJ Int J Neural Syst; 2008 Oct; 18(5):433-41. PubMed ID: 18991365 [TBL] [Abstract][Full Text] [Related]
12. A learning rule for very simple universal approximators consisting of a single layer of perceptrons. Auer P; Burgsteiner H; Maass W Neural Netw; 2008 Jun; 21(5):786-95. PubMed ID: 18249524 [TBL] [Abstract][Full Text] [Related]
13. A new error function at hidden layers for past training of multilayer perceptrons. Oh SH; Lee SY IEEE Trans Neural Netw; 1999; 10(4):960-4. PubMed ID: 18252596 [TBL] [Abstract][Full Text] [Related]
14. Prediction of body mass index in mice using dense molecular markers and a regularized neural network. Okut H; Gianola D; Rosa GJ; Weigel KA Genet Res (Camb); 2011 Jun; 93(3):189-201. PubMed ID: 21481292 [TBL] [Abstract][Full Text] [Related]
15. Novel maximum-margin training algorithms for supervised neural networks. Ludwig O; Nunes U IEEE Trans Neural Netw; 2010 Jun; 21(6):972-84. PubMed ID: 20409990 [TBL] [Abstract][Full Text] [Related]
16. Nonlinear blind source separation using a radial basis function network. Tan Y; Wang J; Zurada JM IEEE Trans Neural Netw; 2001; 12(1):124-34. PubMed ID: 18244368 [TBL] [Abstract][Full Text] [Related]
17. Two-Timescale Multilayer Recurrent Neural Networks for Nonlinear Programming. Wang J; Wang J IEEE Trans Neural Netw Learn Syst; 2022 Jan; 33(1):37-47. PubMed ID: 33108292 [TBL] [Abstract][Full Text] [Related]
18. Sensitivity analysis of multilayer perceptron to input and weight perturbations. Zeng X; Yeung DS IEEE Trans Neural Netw; 2001; 12(6):1358-66. PubMed ID: 18249965 [TBL] [Abstract][Full Text] [Related]