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 *

248 related articles for article (PubMed ID: 30971881)

  • 21. Toward Robust Cognitive 3D Brain-Inspired Cross-Paradigm System.
    Ben Abdallah A; Dang KN
    Front Neurosci; 2021; 15():690208. PubMed ID: 34248491
    [TBL] [Abstract][Full Text] [Related]  

  • 22. MorphIC: A 65-nm 738k-Synapse/mm
    Frenkel C; Legat JD; Bol D
    IEEE Trans Biomed Circuits Syst; 2019 Oct; 13(5):999-1010. PubMed ID: 31329562
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Efficient Synapse Memory Structure for Reconfigurable Digital Neuromorphic Hardware.
    Kim J; Koo J; Kim T; Kim JJ
    Front Neurosci; 2018; 12():829. PubMed ID: 30515074
    [TBL] [Abstract][Full Text] [Related]  

  • 24. A learning theory for reward-modulated spike-timing-dependent plasticity with application to biofeedback.
    Legenstein R; Pecevski D; Maass W
    PLoS Comput Biol; 2008 Oct; 4(10):e1000180. PubMed ID: 18846203
    [TBL] [Abstract][Full Text] [Related]  

  • 25. 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]  

  • 26. 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]  

  • 27. Event-driven implementation of deep spiking convolutional neural networks for supervised classification using the SpiNNaker neuromorphic platform.
    Patiño-Saucedo A; Rostro-Gonzalez H; Serrano-Gotarredona T; Linares-Barranco B
    Neural Netw; 2020 Jan; 121():319-328. PubMed ID: 31590013
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Mimicking Biological Synaptic Functionality with an Indium Phosphide Synaptic Device on Silicon for Scalable Neuromorphic Computing.
    Sarkar D; Tao J; Wang W; Lin Q; Yeung M; Ren C; Kapadia R
    ACS Nano; 2018 Feb; 12(2):1656-1663. PubMed ID: 29328623
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Highly efficient neuromorphic learning system of spiking neural network with multi-compartment leaky integrate-and-fire neurons.
    Gao T; Deng B; Wang J; Yi G
    Front Neurosci; 2022; 16():929644. PubMed ID: 36248664
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Neuromorphic implementations of neurobiological learning algorithms for spiking neural networks.
    Walter F; Röhrbein F; Knoll A
    Neural Netw; 2015 Dec; 72():152-67. PubMed ID: 26422422
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Obstacle Avoidance and Target Acquisition for Robot Navigation Using a Mixed Signal Analog/Digital Neuromorphic Processing System.
    Milde MB; Blum H; Dietmüller A; Sumislawska D; Conradt J; Indiveri G; Sandamirskaya Y
    Front Neurorobot; 2017; 11():28. PubMed ID: 28747883
    [TBL] [Abstract][Full Text] [Related]  

  • 32. A 22-pJ/spike 73-Mspikes/s 130k-compartment neural array transceiver with conductance-based synaptic and membrane dynamics.
    Park J; Ha S; Yu T; Neftci E; Cauwenberghs G
    Front Neurosci; 2023; 17():1198306. PubMed ID: 37700751
    [TBL] [Abstract][Full Text] [Related]  

  • 33. All-memristive neuromorphic computing with level-tuned neurons.
    Pantazi A; Woźniak S; Tuma T; Eleftheriou E
    Nanotechnology; 2016 Sep; 27(35):355205. PubMed ID: 27455898
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Breaking Liebig's Law: An Advanced Multipurpose Neuromorphic Engine.
    Wang R; van Schaik A
    Front Neurosci; 2018; 12():593. PubMed ID: 30210278
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Single neuromorphic memristor closely emulates multiple synaptic mechanisms for energy efficient neural networks.
    Weilenmann C; Ziogas AN; Zellweger T; Portner K; Mladenović M; Kaniselvan M; Moraitis T; Luisier M; Emboras A
    Nat Commun; 2024 Aug; 15(1):6898. PubMed ID: 39138160
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Characterization and compensation of network-level anomalies in mixed-signal neuromorphic modeling platforms.
    Petrovici MA; Vogginger B; Müller P; Breitwieser O; Lundqvist M; Muller L; Ehrlich M; Destexhe A; Lansner A; Schüffny R; Schemmel J; Meier K
    PLoS One; 2014; 9(10):e108590. PubMed ID: 25303102
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Extended memory lifetime in spiking neural networks employing memristive synapses with nonlinear conductance dynamics.
    Brivio S; Conti D; Nair MV; Frascaroli J; Covi E; Ricciardi C; Indiveri G; Spiga S
    Nanotechnology; 2019 Jan; 30(1):015102. PubMed ID: 30378572
    [TBL] [Abstract][Full Text] [Related]  

  • 38. A Brain-Inspired Homeostatic Neuron Based on Phase-Change Memories for Efficient Neuromorphic Computing.
    Muñoz-Martin I; Bianchi S; Hashemkhani S; Pedretti G; Melnic O; Ielmini D
    Front Neurosci; 2021; 15():709053. PubMed ID: 34489628
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Emulating synaptic response in n- and p-channel MoS
    Bhattacharjee S; Wigchering R; Manning HG; Boland JJ; Hurley PK
    Sci Rep; 2020 Jul; 10(1):12178. PubMed ID: 32699332
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Indirect and direct training of spiking neural networks for end-to-end control of a lane-keeping vehicle.
    Bing Z; Meschede C; Chen G; Knoll A; Huang K
    Neural Netw; 2020 Jan; 121():21-36. PubMed ID: 31526952
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 13.