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 *

106 related articles for article (PubMed ID: 31962477)

  • 1. Optimal short-term memory before the edge of chaos in driven random recurrent networks.
    Haruna T; Nakajima K
    Phys Rev E; 2019 Dec; 100(6-1):062312. PubMed ID: 31962477
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Real-time computation at the edge of chaos in recurrent neural networks.
    Bertschinger N; Natschläger T
    Neural Comput; 2004 Jul; 16(7):1413-36. PubMed ID: 15165396
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Determination of the Edge of Criticality in Echo State Networks Through Fisher Information Maximization.
    Livi L; Bianchi FM; Alippi C
    IEEE Trans Neural Netw Learn Syst; 2018 Mar; 29(3):706-717. PubMed ID: 28092580
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Information processing in echo state networks at the edge of chaos.
    Boedecker J; Obst O; Lizier JT; Mayer NM; Asada M
    Theory Biosci; 2012 Sep; 131(3):205-13. PubMed ID: 22147532
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Dynamics and Information Import in Recurrent Neural Networks.
    Metzner C; Krauss P
    Front Comput Neurosci; 2022; 16():876315. PubMed ID: 35573264
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Echo state property linked to an input: exploring a fundamental characteristic of recurrent neural networks.
    Manjunath G; Jaeger H
    Neural Comput; 2013 Mar; 25(3):671-96. PubMed ID: 23272918
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Short-term memory in orthogonal neural networks.
    White OL; Lee DD; Sompolinsky H
    Phys Rev Lett; 2004 Apr; 92(14):148102. PubMed ID: 15089576
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Effect of recurrent infomax on the information processing capability of input-driven recurrent neural networks.
    Tanaka T; Nakajima K; Aoyagi T
    Neurosci Res; 2020 Jul; 156():225-233. PubMed ID: 32068068
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Network dynamics for optimal compressive-sensing input-signal recovery.
    Barranca VJ; Kovačič G; Zhou D; Cai D
    Phys Rev E Stat Nonlin Soft Matter Phys; 2014 Oct; 90(4):042908. PubMed ID: 25375568
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Information processing in bacteria: memory, computation, and statistical physics: a key issues review.
    Lan G; Tu Y
    Rep Prog Phys; 2016 May; 79(5):052601. PubMed ID: 27058315
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Computational analysis of memory capacity in echo state networks.
    Farkaš I; Bosák R; Gergeľ P
    Neural Netw; 2016 Nov; 83():109-120. PubMed ID: 27599031
    [TBL] [Abstract][Full Text] [Related]  

  • 12. [Dynamic paradigm in psychopathology: "chaos theory", from physics to psychiatry].
    Pezard L; Nandrino JL
    Encephale; 2001; 27(3):260-8. PubMed ID: 11488256
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Fisher information at the edge of chaos in random Boolean networks.
    Wang XR; Lizier JT; Prokopenko M
    Artif Life; 2011; 17(4):315-29. PubMed ID: 21762019
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Selectively grouping neurons in recurrent networks of lateral inhibition.
    Xie X; Hahnloser RH; Seung HS
    Neural Comput; 2002 Nov; 14(11):2627-46. PubMed ID: 12433293
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Short-term memory capacity in networks via the restricted isometry property.
    Charles AS; Yap HL; Rozell CJ
    Neural Comput; 2014 Jun; 26(6):1198-235. PubMed ID: 24684446
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Memory traces in dynamical systems.
    Ganguli S; Huh D; Sompolinsky H
    Proc Natl Acad Sci U S A; 2008 Dec; 105(48):18970-5. PubMed ID: 19020074
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Computational capabilities of random automata networks for reservoir computing.
    Snyder D; Goudarzi A; Teuscher C
    Phys Rev E Stat Nonlin Soft Matter Phys; 2013 Apr; 87(4):042808. PubMed ID: 23679474
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Simultaneous multichannel signal transfers via chaos in a recurrent neural network.
    Soma K; Mori R; Sato R; Furumai N; Nara S
    Neural Comput; 2015 May; 27(5):1083-101. PubMed ID: 25734496
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Quantitative analysis of nonlinear optical input/output of a quantum-dot network based on the echo state property.
    Tate N; Miyata Y; Sakai SI; Nakamura A; Shimomura S; Nishimura T; Kozuka J; Ogura Y; Tanida J
    Opt Express; 2022 Apr; 30(9):14669-14676. PubMed ID: 35473206
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Orientation tuning properties of simple cells in area V1 derived from an approximate analysis of nonlinear neural field models.
    Wennekers T
    Neural Comput; 2001 Aug; 13(8):1721-47. PubMed ID: 11506668
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.