BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

337 related articles for article (PubMed ID: 31731044)

  • 1. Perceptrons from memristors.
    Silva F; Sanz M; Seixas J; Solano E; Omar Y
    Neural Netw; 2020 Feb; 122():273-278. PubMed ID: 31731044
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Neuromorphic computation with spiking memristors: habituation, experimental instantiation of logic gates and a novel sequence-sensitive perceptron model.
    Gale EM
    Faraday Discuss; 2019 Feb; 213(0):521-551. PubMed ID: 30418449
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. Memristors for Neuromorphic Circuits and Artificial Intelligence Applications.
    Miranda E; Suñé J
    Materials (Basel); 2020 Feb; 13(4):. PubMed ID: 32093164
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Emerging Memristive Artificial Synapses and Neurons for Energy-Efficient Neuromorphic Computing.
    Choi S; Yang J; Wang G
    Adv Mater; 2020 Dec; 32(51):e2004659. PubMed ID: 33006204
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Training memristor-based multilayer neuromorphic networks with SGD, momentum and adaptive learning rates.
    Yan Z; Chen J; Hu R; Huang T; Chen Y; Wen S
    Neural Netw; 2020 Aug; 128():142-149. PubMed ID: 32446191
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Implementation of a spike-based perceptron learning rule using TiO2-x memristors.
    Mostafa H; Khiat A; Serb A; Mayr CG; Indiveri G; Prodromakis T
    Front Neurosci; 2015; 9():357. PubMed ID: 26483629
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Versatile memristor for memory and neuromorphic computing.
    Guo T; Pan K; Jiao Y; Sun B; Du C; Mills JP; Chen Z; Zhao X; Wei L; Zhou YN; Wu YA
    Nanoscale Horiz; 2022 Feb; 7(3):299-310. PubMed ID: 35064257
    [TBL] [Abstract][Full Text] [Related]  

  • 9. STDP and STDP variations with memristors for spiking neuromorphic learning systems.
    Serrano-Gotarredona T; Masquelier T; Prodromakis T; Indiveri G; Linares-Barranco B
    Front Neurosci; 2013; 7():2. PubMed ID: 23423540
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Training and operation of an integrated neuromorphic network based on metal-oxide memristors.
    Prezioso M; Merrikh-Bayat F; Hoskins BD; Adam GC; Likharev KK; Strukov DB
    Nature; 2015 May; 521(7550):61-4. PubMed ID: 25951284
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Learning to Approximate Functions Using Nb-Doped SrTiO
    Tiotto TF; Goossens AS; Borst JP; Banerjee T; Taatgen NA
    Front Neurosci; 2020; 14():627276. PubMed ID: 33679290
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Quantum memristors.
    Pfeiffer P; Egusquiza IL; Di Ventra M; Sanz M; Solano E
    Sci Rep; 2016 Jul; 6():29507. PubMed ID: 27381511
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Nanoscale memristor device as synapse in neuromorphic systems.
    Jo SH; Chang T; Ebong I; Bhadviya BB; Mazumder P; Lu W
    Nano Lett; 2010 Apr; 10(4):1297-301. PubMed ID: 20192230
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A magnetic synapse: multilevel spin-torque memristor with perpendicular anisotropy.
    Lequeux S; Sampaio J; Cros V; Yakushiji K; Fukushima A; Matsumoto R; Kubota H; Yuasa S; Grollier J
    Sci Rep; 2016 Aug; 6():31510. PubMed ID: 27539144
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Integration of nanoscale memristor synapses in neuromorphic computing architectures.
    Indiveri G; Linares-Barranco B; Legenstein R; Deligeorgis G; Prodromakis T
    Nanotechnology; 2013 Sep; 24(38):384010. PubMed ID: 23999381
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Memristor-Based Neuromorphic Chips.
    Duan X; Cao Z; Gao K; Yan W; Sun S; Zhou G; Wu Z; Ren F; Sun B
    Adv Mater; 2024 Apr; 36(14):e2310704. PubMed ID: 38168750
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Data Clustering using Memristor Networks.
    Choi S; Sheridan P; Lu WD
    Sci Rep; 2015 May; 5():10492. PubMed ID: 26020412
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Analysis of the Memristor-Based Crossbar Synapse for Neuromorphic Systems.
    Kim B; Jo S; Sun W; Shin H
    J Nanosci Nanotechnol; 2019 Oct; 19(10):6703-6709. PubMed ID: 31027014
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Linear conductance update improvement of CMOS-compatible second-order memristors for fast and energy-efficient training of a neural network using a memristor crossbar array.
    Park SO; Park T; Jeong H; Hong S; Seo S; Kwon Y; Lee J; Choi S
    Nanoscale Horiz; 2023 Sep; 8(10):1366-1376. PubMed ID: 37403772
    [TBL] [Abstract][Full Text] [Related]  

  • 20. MoS
    Li D; Wu B; Zhu X; Wang J; Ryu B; Lu WD; Lu W; Liang X
    ACS Nano; 2018 Sep; 12(9):9240-9252. PubMed ID: 30192507
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 17.