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Jianfeng Feng: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Jianfeng Feng, David Brown
    What is observable in a class of neurodynamics? [Citation Graph (0, 0)][DBLP]
    ESANN, 1998, pp:149-154 [Conf]
  2. Jianfeng Feng, Brunello Tirozzi, David Brown
    Output jitter diverges to infinity, converges to zero or remains constant. [Citation Graph (0, 0)][DBLP]
    ESANN, 1998, pp:39-48 [Conf]
  3. Phill Rowcliffe, Jianfeng Feng, Hilary Buxton
    Clustering within Integrate-and-Fire Neurons for Image Segmentation. [Citation Graph (0, 0)][DBLP]
    ICANN, 2002, pp:69-74 [Conf]
  4. Peter Williams, Sheng Li, Jianfeng Feng, Si Wu
    Scaling the Kernel Function to Improve Performance of the Support Vector Machine. [Citation Graph (0, 0)][DBLP]
    ISNN (1), 2005, pp:831-836 [Conf]
  5. Si Wu, Jianfeng Feng, Shun-ichi Amari
    The Ideal Noisy Environment for Fast Neural Computation. [Citation Graph (0, 0)][DBLP]
    ISNN (1), 2006, pp:1-6 [Conf]
  6. David Brown, Jianfeng Feng
    Effects of Correlation and Degree of Balance in Random Synaptic Inputs on the Output of the Hodgkin-Huxley Model. [Citation Graph (0, 0)][DBLP]
    IWANN (1), 1999, pp:197-205 [Conf]
  7. Andrew Davison, Jianfeng Feng, David Brown
    Structure of Lateral Inhibition in an Olfactory Bulb Model. [Citation Graph (0, 0)][DBLP]
    IWANN (1), 1999, pp:189-196 [Conf]
  8. Stuart Feerick, Jianfeng Feng, David Brown
    Paradoxical Relationship between Output and Input Regularity for the FitzHugh-Nagumo Model. [Citation Graph (0, 0)][DBLP]
    IWANN (1), 1999, pp:221-229 [Conf]
  9. Jianfeng Feng
    Neuronal Models with Current Inputs. [Citation Graph (0, 0)][DBLP]
    IWANN (1), 2001, pp:47-54 [Conf]
  10. Jianfeng Feng
    Non-symmetric Support Vector Machines. [Citation Graph (0, 0)][DBLP]
    IWANN (1), 2001, pp:418-426 [Conf]
  11. Jianfeng Feng
    The Minimum-Variance Theory Revisited. [Citation Graph (0, 0)][DBLP]
    IWANN (1), 2003, pp:62-69 [Conf]
  12. Jianfeng Feng
    Integrate-and-Fire Model with Correlated Inputs. [Citation Graph (0, 0)][DBLP]
    IWANN (1), 1999, pp:258-267 [Conf]
  13. Jianfeng Feng
    Estimating Exact Form of Generalisation Errors. [Citation Graph (0, 0)][DBLP]
    IWANN (1), 1999, pp:413-420 [Conf]
  14. Jianfeng Feng, David Brown
    Viewing a Class of Neurodynamics on Parameter Space. [Citation Graph (0, 0)][DBLP]
    IWANN, 1997, pp:546-555 [Conf]
  15. Jianfeng Feng, Brunello Tirozzi
    An Application of the Saturated Attractor Analysis to Three Typical Models. [Citation Graph (0, 0)][DBLP]
    IWANN, 1995, pp:353-360 [Conf]
  16. Jianfeng Feng, Hong Pan, Vwani P. Roychowdhury
    A Rigorous Analysis of Linsker-Type Hebbian Learning. [Citation Graph (0, 0)][DBLP]
    NIPS, 1994, pp:319-326 [Conf]
  17. Zimbul Albo, Gonzalo Viana Di Prisco, Yonghong Chen, Govindan Rangarajan, Wilson A. Truccolo, Jianfeng Feng, Robert P. Vertes, Mingzhou Ding
    Is partial coherence a viable technique for identifying generators of neural oscillations? [Citation Graph (0, 0)][DBLP]
    Biological Cybernetics, 2004, v:90, n:5, pp:318-326 [Journal]
  18. Benoit Gaillard, Hilary Buxton, Jianfeng Feng
    Population approach to a neural discrimination task. [Citation Graph (0, 0)][DBLP]
    Biological Cybernetics, 2006, v:94, n:3, pp:180-191 [Journal]
  19. Simon Durrant, Jianfeng Feng
    Negatively correlated firing: the functional meaning of lateral inhibition within cortical columns. [Citation Graph (0, 0)][DBLP]
    Biological Cybernetics, 2006, v:95, n:5, pp:431-453 [Journal]
  20. David Brown, Jianfeng Feng
    Low correlation between random synaptic inputs impacts considerably on the output of the Hodgkin-Huxley model. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2000, v:32, n:, pp:61-66 [Journal]
  21. David Brown, Jianfeng Feng
    Is there a problem matching real and model CV(ISI)? [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 1999, v:26, n:, pp:87-91 [Journal]
  22. David Brown, Stuart Feerick, Jianfeng Feng
    Significance of random neuronal drive. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2001, v:38, n:, pp:111-119 [Journal]
  23. Andrew Davison, Jianfeng Feng, David Brown
    Spike synchronization in a biophysically-detailed model of the olfactory bulb. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2001, v:38, n:, pp:515-521 [Journal]
  24. Guibin Li, Jianfeng Feng
    Stimulus-evoked synchronization in neuronal models. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2004, v:58, n:, pp:203-208 [Journal]
  25. Stuart Feerick, Jianfeng Feng, David Brown
    Random pulse input versus continuous current plus white noise: Are they equivalent? [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2000, v:32, n:, pp:127-132 [Journal]
  26. Stuart Feerick, Jianfeng Feng, David Brown
    Inhibitory inputs increase a neurons's firing rate. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2001, v:38, n:, pp:197-203 [Journal]
  27. Jianfeng Feng
    Synchronization driven by correlated inputs. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2000, v:32, n:, pp:371-378 [Journal]
  28. Jianfeng Feng
    Training neuron models with the Informax principle. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2002, v:44, n:, pp:97-101 [Journal]
  29. Jianfeng Feng
    Origin of firing varibility of the integrate-and-fire model. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 1999, v:26, n:, pp:117-122 [Journal]
  30. Jianfeng Feng, Guibin Li
    Behaviour of two-compartment models. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2001, v:38, n:, pp:205-211 [Journal]
  31. Jianfeng Feng, Brunello Tirozzi
    Convergence theorems for a class of learning algorithms with VLRPs. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 1997, v:15, n:1, pp:45-68 [Journal]
  32. Jianfeng Feng, Brunello Tirozzi
    A discrete version of the dynamic link network. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 1997, v:15, n:2, pp:91-106 [Journal]
  33. Ping Zhang, Jianfeng Feng
    Ideal observer of single neuron activity. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2002, v:44, n:, pp:243-247 [Journal]
  34. Jianfeng Feng
    Lyapunov Functions for Neural Nets with Nondifferentiable Input-Output Characteristics. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 1997, v:9, n:1, pp:43-49 [Journal]
  35. Jianfeng Feng, David Brown
    Impact of Correlated Inputs on the Output of the Integrate-and-Fire Model. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2000, v:12, n:3, pp:671-692 [Journal]
  36. Jianfeng Feng, David Brown
    Fixed Point Attractor Analysis for a Class of Neurodynamics. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 1998, v:10, n:1, pp:189-214 [Journal]
  37. Jianfeng Feng, Guibin Li
    Impact of Geometrical Structures on the Output of Neuronal Models: A Theoretical and Numerical Analysis. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2002, v:14, n:3, pp:621-640 [Journal]
  38. Jianfeng Feng
    Is the integrate-and-fire model good enough?--a review. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2001, v:14, n:6-7, pp:955-975 [Journal]
  39. Jianfeng Feng, Hong Pan, Vwani P. Roychowdhury
    Linsker-type Hebbian Learning: A Qualitative Analysis on the Parameter Space. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 1997, v:10, n:4, pp:705-720 [Journal]
  40. Jianfeng Feng, David Brown
    A Novel Approach for Analyzing Dynamics in Neural Networks with Saturated Characteristics. [Citation Graph (0, 0)][DBLP]
    Neural Processing Letters, 1996, v:4, n:1, pp:9-16 [Journal]
  41. Enrico Rossoni, Jianfeng Feng
    Decoding spike train ensembles: tracking a moving stimulus. [Citation Graph (0, 0)][DBLP]
    Biological Cybernetics, 2007, v:96, n:1, pp:99-112 [Journal]

  42. On Modularity of Social Network Communities: The Spectral Characterization. [Citation Graph (, )][DBLP]


  43. Coefficient of variation of interspike intervals greater than 0.5. How and when? [Citation Graph (, )][DBLP]


  44. Impact of temporal variation and the balance between excitation and inhibition on the output of the perfect integrate-and-fire model. [Citation Graph (, )][DBLP]


  45. A novel approach to detect hot-spots in large-scale multivariate data. [Citation Graph (, )][DBLP]


  46. A machine learning approach to explore the spectra intensity pattern of peptides using tandem mass spectrometry data. [Citation Graph (, )][DBLP]


  47. Granger causality vs. dynamic Bayesian network inference: a comparative study. [Citation Graph (, )][DBLP]


  48. Granger causality vs. dynamic Bayesian network inference: a comparative study. [Citation Graph (, )][DBLP]


  49. Identifying interactions in the time and frequency domains in local and global networks - A Granger Causality Approach. [Citation Graph (, )][DBLP]


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