Estimation of diffusion coefficients from voltammetric signals by support vector and gaussian process regression

  • M. Bogdan, D. Brugger, W. Rosenstiel, B. Speiser
    Estimation of diffusion coefficients from voltammetric signals by support vector and gaussian process regression | LINK

    Journal of Cheminformatics 6:30,  2014

  • T. Schmid, D. Günzel, M. Bogdan
    Automated Quantification of the Relation between Resistor-Capacitor Subcircuits from an Impedance Spectrum | LINK

    Proceedings of the International Conference on Bio-inspired Systems and Signal Processing, pp. 141-148, 2014

  • K. El-Laithy, M. Bogdan
    Synaptic energy drives the information processing mechanisms in spiking neural networks | LINK

    Mathematical Biosciences and Engineering 11(2), 2014

  • T. Schmid, M. Bogdan, D. Günzel
    Discerning Apical and Basolateral Properties of HT-29/B6 and IPEC-J2 Cell Layers by Impedance Spectroscopy, Mathematical Modeling and Machine Learning | LINK

    PLoS ONE 8(7): e62913, 2013

  • K. El-Laithy, M. Knor, J. Käs, M. Bogdan
    Digital Detection and Analysis of Branching and Cell Contacts in Neural Cell Cultures | LINK

    J Neurosci Methods., 210(2):206-19, 2012

  • K. El-Laithy, M. Bogdan
    A Reinforcement Learning Framework for Spiking Networks with Dynamic Synapses

    Computational Intelligence and Neuroscience, vol. 2011, Article ID 869348, 12 pages, doi:10.1155/2011/869348, 2011

  • K. El-Laithy, M. Bogdan
    Synchrony State Generation: an Approach using Stochastic Synapses

    Journal of Artificial Intelligence and Soft Computing Research (JAISCR), Vol. 1, No. 1, pp. 17-25, 2011

  • D. Brugger, W. Rosenstiel, M. Bogdan
    Online SVR Training by Solving the Primal Optimization Problem

    Journal of Signal Processing Systems, pp. 391-402, dx.doi.org/10.1007/s11265-010-0514-5, 2010

  • D. Brugger, W. Rosenstiel, M. Bogdan
    Automatic Cluster Detection in Kohonen’s SOM

    IEEE Transactions on Neural Networks, Vol. 19(3):442-459, 2008

  • M.Bogdan, W. Rosenstiel
    Application of Artificial Neural Networks for Different Engineering Problems

    Lecture Notes in Computer Science 1725, 26th Annual Conference on Current Trends in Theory and Practice of Informatics SOFSEM’99, Milovy, pp. 277-294, 1999, Invited paper