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Journals in DBLP

Neural Networks
2001, volume: 14, number: 10

  1. Antony Browne, Ron Sun
    Connectionist inference models. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2001, v:14, n:10, pp:1331-1355 [Journal]
  2. Mark E. Jackson, Oleg Litvak, James W. Gnadt
    Analysis of the frequency response of the saccadic circuit: numerical simulations. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2001, v:14, n:10, pp:1357-1376 [Journal]
  3. Tianping Chen, Shun-ichi Amari
    Unified stabilization approach to principal and minor components extraction algorithms. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2001, v:14, n:10, pp:1377-1387 [Journal]
  4. Kotaro Hirasawa, Sung-Ho Kim, Jinglu Hu, Junichi Murata, Min Han, Chunzhi Jin
    Improvement of generalization ability for identifying dynamical systems by using universal learning networks. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2001, v:14, n:10, pp:1389-1404 [Journal]
  5. John A. Flanagan
    Self-organization in the one-dimensional SOM with a decreasing neighborhood. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2001, v:14, n:10, pp:1405-1417 [Journal]
  6. Katsuyuki Hagiwara, Taichi Hayasaka, Naohiro Toda, Shiro Usui, Kazuhiro Kuno
    Upper bound of the expected training error of neural network regression for a Gaussian noise sequence. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2001, v:14, n:10, pp:1419-1429 [Journal]
  7. Hiok Chai Quek, Ruowei Zhou
    The POP learning algorithms: reducing work in identifying fuzzy rules. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2001, v:14, n:10, pp:1431-1445 [Journal]
  8. Sergio Bermejo, Joan Cabestany
    Oriented principal component analysis for large margin classifiers. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2001, v:14, n:10, pp:1447-1461 [Journal]
  9. Yuming Chen
    A remark on 'On stability of nonlinear continuous-time neural networks with delays'. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2001, v:14, n:10, pp:1463-0 [Journal]
  10. Michael Schmitt
    On using the Poincaré polynomial for calculating the VC dimension of neural networks. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2001, v:14, n:10, pp:1465-0 [Journal]
  11. Martha A. Carter, Mark E. Oxley
    Response: on using the Poincaré polynomial for calculating the V-C dimension of neural networks. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2001, v:14, n:10, pp:1467-0 [Journal]
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