BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

254 related articles for article (PubMed ID: 16722183)

  • 1. Spiking perceptrons.
    Rowcliffe P; Feng J; Buxton H
    IEEE Trans Neural Netw; 2006 May; 17(3):803-7. PubMed ID: 16722183
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Silicon modeling of the Mihalaş-Niebur neuron.
    Folowosele F; Hamilton TJ; Etienne-Cummings R
    IEEE Trans Neural Netw; 2011 Dec; 22(12):1915-27. PubMed ID: 21990331
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Hardware optimization and serial implementation of a novel spiking neuron model for the POEtic tissue.
    Torres O; Eriksson J; Moreno JM; Villa A
    Biosystems; 2004; 76(1-3):201-8. PubMed ID: 15351143
    [TBL] [Abstract][Full Text] [Related]  

  • 4. 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]  

  • 5. SWAT: a spiking neural network training algorithm for classification problems.
    Wade JJ; McDaid LJ; Santos JA; Sayers HM
    IEEE Trans Neural Netw; 2010 Nov; 21(11):1817-30. PubMed ID: 20876015
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Determination of the number of principal directions in a biologically plausible PCA model.
    Lv JC; Yi Z; Tan KK
    IEEE Trans Neural Netw; 2007 May; 18(3):910-6. PubMed ID: 17526356
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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]  

  • 8. Modeling activity-dependent plasticity in BCM spiking neural networks with application to human behavior recognition.
    Meng Y; Jin Y; Yin J
    IEEE Trans Neural Netw; 2011 Dec; 22(12):1952-66. PubMed ID: 22027373
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Assessment of bioinspired models for pattern recognition in biomimetic systems.
    Pioggia G; Ferro M; Francesco FD; Ahluwalia A; De Rossi D
    Bioinspir Biomim; 2008 Mar; 3():016004. PubMed ID: 18364563
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Recognition of partially occluded and rotated images with a network of spiking neurons.
    Shin JH; Smith D; Swiercz W; Staley K; Rickard JT; Montero J; Kurgan LA; Cios KJ
    IEEE Trans Neural Netw; 2010 Nov; 21(11):1697-709. PubMed ID: 21047704
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Convergence of stochastic learning in perceptrons with binary synapses.
    Senn W; Fusi S
    Phys Rev E Stat Nonlin Soft Matter Phys; 2005 Jun; 71(6 Pt 1):061907. PubMed ID: 16089765
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Synaptic dynamics: linear model and adaptation algorithm.
    Yousefi A; Dibazar AA; Berger TW
    Neural Netw; 2014 Aug; 56():49-68. PubMed ID: 24867390
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Introduction: stability and pattern formation in networks of dynamical systems.
    Boccaletti S; Pecora LM
    Chaos; 2006 Mar; 16(1):015101. PubMed ID: 16599767
    [No Abstract]   [Full Text] [Related]  

  • 14. iSpike: a spiking neural interface for the iCub robot.
    Gamez D; Fidjeland AK; Lazdins E
    Bioinspir Biomim; 2012 Jun; 7(2):025008. PubMed ID: 22617339
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Training spiking neuronal networks with applications in engineering tasks.
    Rowcliffe P; Feng J
    IEEE Trans Neural Netw; 2008 Sep; 19(9):1626-40. PubMed ID: 18779093
    [TBL] [Abstract][Full Text] [Related]  

  • 16. An extended model for a spiking neuron class.
    Guerreiro AM; Paz de Araujo CA
    Biol Cybern; 2007 Sep; 97(3):211-9. PubMed ID: 17647011
    [TBL] [Abstract][Full Text] [Related]  

  • 17. On the classification capability of sign-constrained perceptrons.
    Legenstein R; Maass W
    Neural Comput; 2008 Jan; 20(1):288-309. PubMed ID: 18045010
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Simulating dynamic plastic continuous neural networks by finite elements.
    Joghataie A; Torghabehi OO
    IEEE Trans Neural Netw Learn Syst; 2014 Aug; 25(8):1583-7. PubMed ID: 25050953
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Learning in neural networks by reinforcement of irregular spiking.
    Xie X; Seung HS
    Phys Rev E Stat Nonlin Soft Matter Phys; 2004 Apr; 69(4 Pt 1):041909. PubMed ID: 15169045
    [TBL] [Abstract][Full Text] [Related]  

  • 20. On the almost periodic solution of cellular neural networks with distributed delays.
    Liu Y; You Z; Cao L
    IEEE Trans Neural Netw; 2007 Jan; 18(1):295-300. PubMed ID: 17278480
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 13.