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 *

74 related articles for article (PubMed ID: 18282833)

  • 1. Trellis codes, receptive fields, and fault tolerant, self-repairing neural networks.
    Petsche T; Dickinson BW
    IEEE Trans Neural Netw; 1990; 1(2):154-66. PubMed ID: 18282833
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Maximally fault tolerant neural networks.
    Neti C; Schneider MH; Young ED
    IEEE Trans Neural Netw; 1992; 3(1):14-23. PubMed ID: 18276402
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Source-channel optimized trellis codes for bitonal image transmission over AWGN channels.
    Kroll JM; Phamdo N
    IEEE Trans Image Process; 1999; 8(7):899-912. PubMed ID: 18267503
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Distributed fault tolerance in optimal interpolative nets.
    Simon D
    IEEE Trans Neural Netw; 2001; 12(6):1348-57. PubMed ID: 18249964
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Investigating the fault tolerance of neural networks.
    Tchernev EB; Mulvaney RG; Phatak DS
    Neural Comput; 2005 Jul; 17(7):1646-64. PubMed ID: 15901410
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Fault-Tolerant Algorithms for Connectivity Restoration in Wireless Sensor Networks.
    Zeng Y; Xu L; Chen Z
    Sensors (Basel); 2015 Dec; 16(1):. PubMed ID: 26703616
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Synthesis of fault-tolerant feedforward neural networks using minimax optimization.
    Deodhare D; Vidyasagar M; Sathiya Keethi S
    IEEE Trans Neural Netw; 1998; 9(5):891-900. PubMed ID: 18255774
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Steganographic coding scheme based on dither convolutional trellis under resampling mechanism.
    Cao PC; Liu WW; Liu GJ; Zhai JT; Ji XP; Dai YW
    Math Biosci Eng; 2019 Jun; 16(5):6015-6033. PubMed ID: 31499750
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A fault-tolerant regularizer for RBF networks.
    Leung CS; Sum JP
    IEEE Trans Neural Netw; 2008 Mar; 19(3):493-507. PubMed ID: 18334367
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Encoding binary neural codes in networks of threshold-linear neurons.
    Curto C; Degeratu A; Itskov V
    Neural Comput; 2013 Nov; 25(11):2858-903. PubMed ID: 23895048
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Performance and fault-tolerance of neural networks for optimization.
    Protzel PW; Palumbo DL; Arras MK
    IEEE Trans Neural Netw; 1993; 4(4):600-14. PubMed ID: 18267761
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Novel neural networks-based fault tolerant control scheme with fault alarm.
    Shen Q; Jiang B; Shi P; Lim CC
    IEEE Trans Cybern; 2014 Nov; 44(11):2190-201. PubMed ID: 25014982
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Neural networks with local receptive fields and superlinear VC dimension.
    Schmitt M
    Neural Comput; 2002 Apr; 14(4):919-56. PubMed ID: 11936967
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Convergence and objective functions of some fault/noise-injection-based online learning algorithms for RBF networks.
    Ho KI; Leung CS; Sum J
    IEEE Trans Neural Netw; 2010 Jun; 21(6):938-47. PubMed ID: 20388593
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Combinatorial neural codes from a mathematical coding theory perspective.
    Curto C; Itskov V; Morrison K; Roth Z; Walker JL
    Neural Comput; 2013 Jul; 25(7):1891-925. PubMed ID: 23724797
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Fault-tolerant nonlinear adaptive flight control using sliding mode online learning.
    Krüger T; Schnetter P; Placzek R; Vörsmann P
    Neural Netw; 2012 Aug; 32():267-74. PubMed ID: 22386784
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Masking fields: a massively parallel neural architecture for learning, recognizing, and predicting multiple groupings of patterned data.
    Cohen MA; Grossberg S
    Appl Opt; 1987 May; 26(10):1866-91. PubMed ID: 20454417
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Replicating receptive fields of simple and complex cells in primary visual cortex in a neuronal network model with temporal and population sparseness and reliability.
    Tanaka T; Aoyagi T; Kaneko T
    Neural Comput; 2012 Oct; 24(10):2700-25. PubMed ID: 22845820
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Dynamic switching of neural codes in networks with gap junctions.
    Katori Y; Masuda N; Aihara K
    Neural Netw; 2006 Dec; 19(10):1463-6. PubMed ID: 16887330
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A neural network model on self-organizing emergence of simple-cell receptive field with orientation selectivity in visual cortex.
    Yang Q; Qi X; Wang Y
    Sci China C Life Sci; 2001 Oct; 44(5):469-78. PubMed ID: 18726392
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 4.