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 *

249 related articles for article (PubMed ID: 21442012)

  • 1. On spike-timing-dependent-plasticity, memristive devices, and building a self-learning visual cortex.
    Zamarreño-Ramos C; Camuñas-Mesa LA; Pérez-Carrasco JA; Masquelier T; Serrano-Gotarredona T; Linares-Barranco B
    Front Neurosci; 2011; 5():26. PubMed ID: 21442012
    [TBL] [Abstract][Full Text] [Related]  

  • 2. 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]  

  • 3. Dynamical memristive neural networks and associative self-learning architectures using biomimetic devices.
    Zivasatienraj B; Doolittle WA
    Front Neurosci; 2023; 17():1153183. PubMed ID: 37152603
    [TBL] [Abstract][Full Text] [Related]  

  • 4. 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]  

  • 5. Self-adaptive STDP-based learning of a spiking neuron with nanocomposite memristive weights.
    Emelyanov AV; Nikiruy KE; Serenko AV; Sitnikov AV; Presnyakov MY; Rybka RB; Sboev AG; Rylkov VV; Kashkarov PK; Kovalchuk MV; Demin VA
    Nanotechnology; 2020 Jan; 31(4):045201. PubMed ID: 31578002
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A compound memristive synapse model for statistical learning through STDP in spiking neural networks.
    Bill J; Legenstein R
    Front Neurosci; 2014; 8():412. PubMed ID: 25565943
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Single pairing spike-timing dependent plasticity in BiFeO3 memristors with a time window of 25 ms to 125 μs.
    Du N; Kiani M; Mayr CG; You T; Bürger D; Skorupa I; Schmidt OG; Schmidt H
    Front Neurosci; 2015; 9():227. PubMed ID: 26175666
    [TBL] [Abstract][Full Text] [Related]  

  • 8. 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]  

  • 9. Analog Memristive Synapse in Spiking Networks Implementing Unsupervised Learning.
    Covi E; Brivio S; Serb A; Prodromakis T; Fanciulli M; Spiga S
    Front Neurosci; 2016; 10():482. PubMed ID: 27826226
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Pulse Shape and Timing Dependence on the Spike-Timing Dependent Plasticity Response of Ion-Conducting Memristors as Synapses.
    Campbell KA; Drake KT; Barney Smith EH
    Front Bioeng Biotechnol; 2016; 4():97. PubMed ID: 28083531
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Spike timing-dependent plasticity and memory.
    Debanne D; Inglebert Y
    Curr Opin Neurobiol; 2023 Jun; 80():102707. PubMed ID: 36924615
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Self-Adaptive Spike-Time-Dependent Plasticity of Metal-Oxide Memristors.
    Prezioso M; Merrikh Bayat F; Hoskins B; Likharev K; Strukov D
    Sci Rep; 2016 Feb; 6():21331. PubMed ID: 26893175
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A forecast-based STDP rule suitable for neuromorphic implementation.
    Davies S; Galluppi F; Rast AD; Furber SB
    Neural Netw; 2012 Aug; 32():3-14. PubMed ID: 22386500
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A Hybrid CMOS-Memristor Neuromorphic Synapse.
    Azghadi MR; Linares-Barranco B; Abbott D; Leong PH
    IEEE Trans Biomed Circuits Syst; 2017 Apr; 11(2):434-445. PubMed ID: 28026782
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A CMOS-memristor hybrid system for implementing stochastic binary spike timing-dependent plasticity.
    Ahmadi-Farsani J; Ricci S; Hashemkhani S; Ielmini D; Linares-Barranco B; Serrano-Gotarredona T
    Philos Trans A Math Phys Eng Sci; 2022 Jul; 380(2228):20210018. PubMed ID: 35658675
    [TBL] [Abstract][Full Text] [Related]  

  • 16. An Adaptive STDP Learning Rule for Neuromorphic Systems.
    Gautam A; Kohno T
    Front Neurosci; 2021; 15():741116. PubMed ID: 34630026
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A 2-transistor/1-resistor artificial synapse capable of communication and stochastic learning in neuromorphic systems.
    Wang Z; Ambrogio S; Balatti S; Ielmini D
    Front Neurosci; 2014; 8():438. PubMed ID: 25642161
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Thousands of conductance levels in memristors integrated on CMOS.
    Rao M; Tang H; Wu J; Song W; Zhang M; Yin W; Zhuo Y; Kiani F; Chen B; Jiang X; Liu H; Chen HY; Midya R; Ye F; Jiang H; Wang Z; Wu M; Hu M; Wang H; Xia Q; Ge N; Li J; Yang JJ
    Nature; 2023 Mar; 615(7954):823-829. PubMed ID: 36991190
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A neuromorphic architecture for object recognition and motion anticipation using burst-STDP.
    Nere A; Olcese U; Balduzzi D; Tononi G
    PLoS One; 2012; 7(5):e36958. PubMed ID: 22615855
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Necessary conditions for STDP-based pattern recognition learning in a memristive spiking neural network.
    Demin VA; Nekhaev DV; Surazhevsky IA; Nikiruy KE; Emelyanov AV; Nikolaev SN; Rylkov VV; Kovalchuk MV
    Neural Netw; 2021 Feb; 134():64-75. PubMed ID: 33291017
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 13.