BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

135 related articles for article (PubMed ID: 18276501)

  • 1. Neural subnet design by direct polynomial mapping.
    Rohani K; Chen MS; Manry MT
    IEEE Trans Neural Netw; 1992; 3(6):1024-6. PubMed ID: 18276501
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Fast training of multilayer perceptrons.
    Verma B
    IEEE Trans Neural Netw; 1997; 8(6):1314-20. PubMed ID: 18255733
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Modeling of batch processes using explicitly time-dependent artificial neural networks.
    Ganesh B; Kumar VV; Rani KY
    IEEE Trans Neural Netw Learn Syst; 2014 May; 25(5):970-9. PubMed ID: 24808042
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Accuracy analysis for wavelet approximations.
    Delyon B; Juditsky A; Benveniste A
    IEEE Trans Neural Netw; 1995; 6(2):332-48. PubMed ID: 18263316
    [TBL] [Abstract][Full Text] [Related]  

  • 5. A robust backpropagation learning algorithm for function approximation.
    Chen DS; Jain RC
    IEEE Trans Neural Netw; 1994; 5(3):467-79. PubMed ID: 18267813
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Extracting rules from trained neural networks.
    Tsukimoto H
    IEEE Trans Neural Netw; 2000; 11(2):377-89. PubMed ID: 18249768
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Beyond feedforward models trained by backpropagation: a practical training tool for a more efficient universal approximator.
    Ilin R; Kozma R; Werbos PJ
    IEEE Trans Neural Netw; 2008 Jun; 19(6):929-37. PubMed ID: 18541494
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Modeling of nonlinear nonstationary dynamic systems with a novel class of artificial neural networks.
    Iatrou M; Berger TW; Marmarelis VZ
    IEEE Trans Neural Netw; 1999; 10(2):327-39. PubMed ID: 18252530
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Conventional modeling of the multilayer perceptron using polynomial basis functions.
    Chen MS; Manry MT
    IEEE Trans Neural Netw; 1993; 4(1):164-6. PubMed ID: 18267718
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Universal Approximation Using Feedforward Neural Networks: A Survey of Some Existing Methods, and Some New Results.
    Chung Tsoi A; Scarselli F
    Neural Netw; 1998 Jan; 11(1):15-37. PubMed ID: 12662846
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Global Boltzmann perceptron network for online learning of conditional distributions.
    Thathachar ML; Arvind MT
    IEEE Trans Neural Netw; 1999; 10(5):1090-8. PubMed ID: 18252611
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 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]  

  • 13. Evaluation of convolutional neural networks for visual recognition.
    Nebauer C
    IEEE Trans Neural Netw; 1998; 9(4):685-96. PubMed ID: 18252491
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Learning polynomial feedforward neural networks by genetic programming and backpropagation.
    Nikolaev NY; Iba H
    IEEE Trans Neural Netw; 2003; 14(2):337-50. PubMed ID: 18238017
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Local coupled feedforward neural network.
    Sun J
    Neural Netw; 2010 Jan; 23(1):108-13. PubMed ID: 19596550
    [TBL] [Abstract][Full Text] [Related]  

  • 16. The Chebyshev-polynomials-based unified model neural networks for function approximation.
    Lee TT; Jeng JT
    IEEE Trans Syst Man Cybern B Cybern; 1998; 28(6):925-35. PubMed ID: 18256014
    [TBL] [Abstract][Full Text] [Related]  

  • 17. 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]  

  • 18. Computational capabilities of graph neural networks.
    Scarselli F; Gori M; Tsoi AC; Hagenbuchner M; Monfardini G
    IEEE Trans Neural Netw; 2009 Jan; 20(1):81-102. PubMed ID: 19129034
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Performance evaluation of a sequential minimal radial basis function (RBF) neural network learning algorithm.
    Lu Y; Sundararajan N; Saratchandran P
    IEEE Trans Neural Netw; 1998; 9(2):308-18. PubMed ID: 18252454
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Using function approximation to analyze the sensitivity of MLP with antisymmetric squashing activation function.
    Yeung DS; Sun X
    IEEE Trans Neural Netw; 2002; 13(1):34-44. PubMed ID: 18244407
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.