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 *

311 related articles for article (PubMed ID: 23627657)

  • 1. Adaptive and predictive control of a simulated robot arm.
    Tolu S; Vanegas M; Garrido JA; Luque NR; Ros E
    Int J Neural Syst; 2013 Jun; 23(3):1350010. PubMed ID: 23627657
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Bio-inspired adaptive feedback error learning architecture for motor control.
    Tolu S; Vanegas M; Luque NR; Garrido JA; Ros E
    Biol Cybern; 2012 Oct; 106(8-9):507-22. PubMed ID: 22907270
    [TBL] [Abstract][Full Text] [Related]  

  • 3. From sensors to spikes: evolving receptive fields to enhance sensorimotor information in a robot-arm.
    Luque NR; Garrido JA; Ralli J; Laredo JJ; Ros E
    Int J Neural Syst; 2012 Aug; 22(4):1250013. PubMed ID: 22830963
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Fuzzy neuronal model of motor control inspired by cerebellar pathways to online and gradually learn inverse biomechanical functions in the presence of delay.
    Salimi-Badr A; Ebadzadeh MM; Darlot C
    Biol Cybern; 2017 Dec; 111(5-6):421-438. PubMed ID: 28993878
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Recurrent cerebellar loops simplify adaptive control of redundant and nonlinear motor systems.
    Porrill J; Dean P
    Neural Comput; 2007 Jan; 19(1):170-93. PubMed ID: 17134321
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Adaptive cerebellar spiking model embedded in the control loop: context switching and robustness against noise.
    Luque NR; Garrido JA; Carrillo RR; Tolu S; Ros E
    Int J Neural Syst; 2011 Oct; 21(5):385-401. PubMed ID: 21956931
    [TBL] [Abstract][Full Text] [Related]  

  • 7. An internal model for acquisition and retention of motor learning during arm reaching.
    Lonini L; Dipietro L; Zollo L; Guglielmelli E; Krebs HI
    Neural Comput; 2009 Jul; 21(7):2009-27. PubMed ID: 19323640
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A model of the cerebellar pathways applied to the control of a single-joint robot arm actuated by McKibben artificial muscles.
    Eskiizmirliler S; Forestier N; Tondu B; Darlot C
    Biol Cybern; 2002 May; 86(5):379-94. PubMed ID: 11984652
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A neural model of cerebellar learning for arm movement control: cortico-spino-cerebellar dynamics.
    Contreras-Vidal JL; Grossberg S; Bullock D
    Learn Mem; 1997; 3(6):475-502. PubMed ID: 10456112
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A bi-hemispheric neuronal network model of the cerebellum with spontaneous climbing fiber firing produces asymmetrical motor learning during robot control.
    Pinzon-Morales RD; Hirata Y
    Front Neural Circuits; 2014; 8():131. PubMed ID: 25414644
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Distributed cerebellar plasticity implements adaptable gain control in a manipulation task: a closed-loop robotic simulation.
    Garrido JA; Luque NR; D'Angelo E; Ros E
    Front Neural Circuits; 2013; 7():159. PubMed ID: 24130518
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Cerebellar-inspired adaptive control of a robot eye actuated by pneumatic artificial muscles.
    Lenz A; Anderson SR; Pipe AG; Melhuish C; Dean P; Porrill J
    IEEE Trans Syst Man Cybern B Cybern; 2009 Dec; 39(6):1420-33. PubMed ID: 19369158
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Computation of inverse functions in a model of cerebellar and reflex pathways allows to control a mobile mechanical segment.
    Ebadzadeh M; Tondu B; Darlot C
    Neuroscience; 2005; 133(1):29-49. PubMed ID: 15893629
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Isotropic-sequence-order learning in a closed-loop behavioural system.
    Porr B; Wörgötter F
    Philos Trans A Math Phys Eng Sci; 2003 Oct; 361(1811):2225-44. PubMed ID: 14599317
    [TBL] [Abstract][Full Text] [Related]  

  • 15. On Robot Compliance: A Cerebellar Control Approach.
    Abadia I; Naveros F; Garrido JA; Ros E; Luque NR
    IEEE Trans Cybern; 2021 May; 51(5):2476-2489. PubMed ID: 31647453
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Human-Like Behavior Generation Based on Head-Arms Model for Robot Tracking External Targets and Body Parts.
    Zhang Z; Beck A; Magnenat-Thalmann N
    IEEE Trans Cybern; 2015 Aug; 45(8):1390-400. PubMed ID: 25252290
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Realtime cerebellum: a large-scale spiking network model of the cerebellum that runs in realtime using a graphics processing unit.
    Yamazaki T; Igarashi J
    Neural Netw; 2013 Nov; 47():103-11. PubMed ID: 23434303
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Cerebellarlike corrective model inference engine for manipulation tasks.
    Luque NR; Garrido JA; Carrillo RR; Coenen OJ; Ros E
    IEEE Trans Syst Man Cybern B Cybern; 2011 Oct; 41(5):1299-312. PubMed ID: 21536535
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Saccade control in a simulated robot camera-head system: neural net architectures for efficient learning of inverse kinematics.
    Dean P; Mayhew JE; Thacker N; Langdon PM
    Biol Cybern; 1991; 66(1):27-36. PubMed ID: 1768710
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Reinforcement learning of motor skills with policy gradients.
    Peters J; Schaal S
    Neural Netw; 2008 May; 21(4):682-97. PubMed ID: 18482830
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 16.