Samuel Johnson

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Samuel Johnson

Dr.

Accepting PhD Students

PhD projects

Complex systems, graphs and networks, computational neuroscience, theoretical ecology

20082024

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  • 2011

    Why are so many networks disassortative?

    Johnson, S., Torres, J. J., Marro, J. & Muñoz, M. A., 2011, Non-Equilibrium Statistical Physics Today - Proceedings of the 11th Granada Seminar on Computational and Statistical Physics. p. 249-250 2 p. (AIP Conference Proceedings; vol. 1332).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • 2010

    Shannon entropy and degree correlations in complex networks

    Johnson, S., Torres, J. J., Marro, J. & Muñoz, M. A., 2010, 10th WSEAS International Conference on Wavelet Analysis and Multirate Systems, WAMUS '10, 9th WSEAS International Conference on Non-Linear Analysis, Non-Linear Systems and Chaos, NOLASC '10. p. 31-35 5 p. (10th WSEAS International Conference on Wavelet Analysis and Multirate Systems, WAMUS '10, 9th WSEAS International Conference on Non-Linear Analysis, Non-Linear Systems and Chaos, NOLASC '10).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • 2009

    Development of neural network structure with biological mechanisms

    Johnson, S., Marro, J., Mejias, J. F. & Torres, J. J., 2009, Bio-Inspired Systems: Computational and Ambient Intelligence - 10th International Work-Conference on Artificial Neural Networks, IWANN 2009, Proceedings. PART 1 ed. p. 228-235 8 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 5517 LNCS, no. PART 1).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Switching dynamics of neural systems in the presence of multiplicative colored noise

    Mejias, J. F., Torres, J. J., Johnson, S. & Kappen, H. J., 2009, Bio-Inspired Systems: Computational and Ambient Intelligence - 10th International Work-Conference on Artificial Neural Networks, IWANN 2009, Proceedings. PART 1 ed. p. 17-23 7 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 5517 LNCS, no. PART 1).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution