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.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

86 related articles for article (PubMed ID: 18282824)

  • 1. Sensitivity of feedforward neural networks to weight errors.
    Stevenson M; Winter R; Widrow B
    IEEE Trans Neural Netw; 1990; 1(1):71-80. PubMed ID: 18282824
    [TBL] [Abstract][Full Text] [Related]  

  • 2. 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]  

  • 3. Sensitivity analysis of single hidden-layer neural networks with threshold functions.
    Oh SH; Lee Y
    IEEE Trans Neural Netw; 1995; 6(4):1005-7. PubMed ID: 18263389
    [TBL] [Abstract][Full Text] [Related]  

  • 4. On the approximation by single hidden layer feedforward neural networks with fixed weights.
    Guliyev NJ; Ismailov VE
    Neural Netw; 2018 Feb; 98():296-304. PubMed ID: 29301110
    [TBL] [Abstract][Full Text] [Related]  

  • 5. An orthogonal neural network for function approximation.
    Yang SS; Tseng CS
    IEEE Trans Syst Man Cybern B Cybern; 1996; 26(5):779-85. PubMed ID: 18263076
    [TBL] [Abstract][Full Text] [Related]  

  • 6. The selection of weight accuracies for Madalines.
    Piche SW
    IEEE Trans Neural Netw; 1995; 6(2):432-45. PubMed ID: 18263325
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Capabilities of a four-layered feedforward neural network: four layers versus three.
    Tamura S; Tateishi M
    IEEE Trans Neural Netw; 1997; 8(2):251-5. PubMed ID: 18255629
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Synthesis of feedforward networks in supremum error bound.
    Ciesielski K; Sacha JP; Cios KJ
    IEEE Trans Neural Netw; 2000; 11(6):1213-27. PubMed ID: 18249848
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Oscillatorylike behavior in feedforward neuronal networks.
    Payeur A; Maler L; Longtin A
    Phys Rev E Stat Nonlin Soft Matter Phys; 2015 Jul; 92(1):012703. PubMed ID: 26274199
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Existence and uniqueness results for neural network approximations.
    Williamson RC; Helmke U
    IEEE Trans Neural Netw; 1995; 6(1):2-13. PubMed ID: 18263280
    [TBL] [Abstract][Full Text] [Related]  

  • 11. 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]  

  • 12. The effects of limited-precision weights on the threshold Adaline.
    Stevenson M
    IEEE Trans Neural Netw; 1997; 8(3):549-52. PubMed ID: 18255658
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Architecture-independent approximation of functions.
    Ruiz De Angulo V; Torras C
    Neural Comput; 2001 May; 13(5):1119-35. PubMed ID: 11359647
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Learning algorithms for feedforward networks based on finite samples.
    Rao NV; Protopopescu V; Mann RC; Oblow EM; Iyengar SS
    IEEE Trans Neural Netw; 1996; 7(4):926-40. PubMed ID: 18263488
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Shot-noise-limited performance of optical neural networks.
    Hayat MM; Saleh BA; Gubner JA
    IEEE Trans Neural Netw; 1996; 7(3):700-8. PubMed ID: 18263466
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Function approximation with spiked random networks.
    Gelenbe E; Mao ZH; Li YD
    IEEE Trans Neural Netw; 1999; 10(1):3-9. PubMed ID: 18252498
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Guaranteed approximation error estimation of neural networks and model modification.
    Yang Y; Wang T; Woolard JP; Xiang W
    Neural Netw; 2022 Jul; 151():61-69. PubMed ID: 35395513
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Reinforcement and backpropagation training for an optical neural network using self-lensing effects.
    Cruz-Cabrera AA; Yang M; Cui G; Behrman EC; Steck JE; Skinner SR
    IEEE Trans Neural Netw; 2000; 11(6):1450-7. PubMed ID: 18249868
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Training pi-sigma network by online gradient algorithm with penalty for small weight update.
    Xiong Y; Wu W; Kang X; Zhang C
    Neural Comput; 2007 Dec; 19(12):3356-68. PubMed ID: 17970657
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Some structural determinants of Pavlovian conditioning in artificial neural networks.
    Sánchez JM; Galeazzi JM; Burgos JE
    Behav Processes; 2010 May; 84(1):526-35. PubMed ID: 20117190
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 5.