| 2008 |
| 34 | EE | Matthias Ihrke,
Hecke Schrobsdorff,
J. Michael Herrmann:
Compensation for Speed-of-Processing Effects in EEG-Data Analysis.
IDEAL 2008: 354-361 |
| 33 | EE | Marotesa Voultsidou,
J. Michael Herrmann:
Statistical Baselines from Random Matrix Theory.
IDEAL 2008: 362-369 |
| 32 | EE | Georg Martius,
Katja Fiedler,
J. Michael Herrmann:
Structure from behavior in autonomous agents.
IROS 2008: 858-862 |
| 31 | EE | Georg Martius,
Stefano Nolfi,
J. Michael Herrmann:
Emergence of Interaction among Adaptive Agents.
SAB 2008: 457-466 |
| 30 | EE | Norbert Michael Mayer,
Matthew Browne,
J. Michael Herrmann,
Minoru Asada:
Symmetries, non-Euclidean metrics, and patterns in a Swift-Hohenberg model of the visual cortex.
Biological Cybernetics 99(1): 63-78 (2008) |
| 29 | EE | Joachim Haß,
Stefan Blaschke,
Thomas Rammsayer,
J. Michael Herrmann:
A neurocomputational model for optimal temporal processing.
Journal of Computational Neuroscience 25(3): 449-464 (2008) |
| 2007 |
| 28 | EE | Georg Martius,
J. Michael Herrmann,
Ralf Der:
Guided Self-organisation for Autonomous Robot Development.
ECAL 2007: 766-775 |
| 27 | EE | J. Michael Herrmann,
Fabian J. Theis:
Statistical Analysis of Sample-Size Effects in ICA.
IDEAL 2007: 416-425 |
| 26 | EE | Hecke Schrobsdorff,
Matthias Ihrke,
B. Kabisch,
J. Behrendt,
M. Hasselhorn,
J. Michael Herrmann:
A computational approach to negative priming.
Connect. Sci. 19(3): 203-221 (2007) |
| 25 | EE | Hecke Schrobsdorff,
J. Michael Herrmann,
Theo Geisel:
A feature-binding model with localized excitations.
Neurocomputing 70(10-12): 1706-1710 (2007) |
| 24 | EE | Anna Levina,
Udo Ernst,
J. Michael Herrmann:
Criticality of avalanche dynamics in adaptive recurrent networks.
Neurocomputing 70(10-12): 1877-1881 (2007) |
| 2005 |
| 23 | EE | Anna Levina,
J. Michael Herrmann,
Theo Geisel:
Dynamical Synapses Give Rise to a Power-Law Distribution of Neuronal Avalanches.
NIPS 2005 |
| 22 | EE | Marotesa Voultsidou,
Silke Dodel,
J. Michael Herrmann:
Neural Networks Approach to Clustering of Activity in fMRI Data.
IEEE Trans. Med. Imaging 24(8): 987-996 (2005) |
| 21 | EE | J. Michael Herrmann,
Hecke Schrobsdorff,
Theo Geisel:
Localized activations in a simple neural field model.
Neurocomputing 65-66: 679-684 (2005) |
| 2004 |
| 20 | | Marotesa Voultsidou,
Silke Dodel,
J. Michael Herrmann:
Analysis of Correlated Activity in fMRI Data by Artificial Neural Networks.
ISBI 2004: 872-875 |
| 2003 |
| 19 | EE | Norbert Michael Mayer,
J. Michael Herrmann,
Theo Geisel:
Shaping of Receptive Fields in the Visual Cortex During Retinal Maturation.
Journal of Computational Neuroscience 15(3): 307-320 (2003) |
| 2002 |
| 18 | EE | Silke Dodel,
J. Michael Herrmann,
Theo Geisel:
Functional connectivity by cross-correlation clustering.
Neurocomputing 44-46: 1065-1070 (2002) |
| 17 | EE | Dmitri Bibitchkov,
J. Michael Herrmann,
Theo Geisel:
Effects of short-time plasticity on the associative memory.
Neurocomputing 44-46: 329-335 (2002) |
| 16 | EE | Norbert Michael Mayer,
J. Michael Herrmann,
Theo Geisel:
Curved feature metrics in models of visual cortex.
Neurocomputing 44-46: 533-539 (2002) |
| 2001 |
| 15 | EE | Silke Dodel,
J. Michael Herrmann,
Theo Geisel:
Stimulus-Independent Data Analysis for fMRI.
Emergent Neural Computational Architectures Based on Neuroscience 2001: 39-53 |
| 14 | EE | Norbert Michael Mayer,
J. Michael Herrmann,
Theo Geisel:
Signatures of natural image statistics in cortical simple cell receptive fields.
Neurocomputing 38-40: 279-284 (2001) |
| 2000 |
| 13 | EE | Dmitri Bibitchkov,
J. Michael Herrmann,
Theo Geisel:
Synaptic Depression in Associative Memory Networks.
IJCNN (5) 2000: 50-58 |
| 12 | EE | Norbert Michael Mayer,
J. Michael Herrmann,
Theo Geisel:
Structure Formation in Visual Cortex Based on a Curved Feature Space.
IJCNN (6) 2000: 153-158 |
| 11 | EE | Norbert Michael Mayer,
J. Michael Herrmann,
Theo Geisel:
Retinotopy and spatial phase in topographic maps.
Neurocomputing 32-33: 447-452 (2000) |
| 10 | EE | Silke Dodel,
J. Michael Herrmann,
Theo Geisel:
Localization of brain activity - blind separation for fMRI data.
Neurocomputing 32-33: 701-708 (2000) |
| 9 | EE | J. Michael Herrmann,
Klaus Pawelzik,
Theo Geisel:
Learning predictive representations.
Neurocomputing 32-33: 785-791 (2000) |
| 1999 |
| 8 | | J. Michael Herrmann,
Klaus Pawelzik,
Theo Geisel:
Self-Localization of Autonomous Robots by Hidden Representations.
Auton. Robots 7(1): 31-40 (1999) |
| 7 | EE | Hans-Ulrich Bauer,
J. Michael Herrmann,
Thomas Villmann:
Neural maps and topographic vector quantization.
Neural Networks 12(4-5): 659-676 (1999) |
| 6 | EE | J. Michael Herrmann,
Klaus Pawelzik:
Simultaneous self-organization of place and direction selectivity in a neural model of self-localization.
Neurocomputing 26-27: 721-727 (1999) |
| 1998 |
| 5 | EE | Thomas Villmann,
J. Michael Herrmann:
Magnification control in neural maps.
ESANN 1998: 191-196 |
| 1997 |
| 4 | | J. Michael Herrmann,
Hans-Ulrich Bauer,
Thomas Villmann:
Measuring topology preservation in maps of real-world data.
ESANN 1997 |
| 3 | | J. Michael Herrmann,
Thomas Villmann:
Vector Quantization by Optimal Neural Gas.
ICANN 1997: 625-630 |
| 1996 |
| 2 | | Ralf Der,
Gerd Balzuweit,
J. Michael Herrmann:
Building Nonlinear Data Models with Self-Organizing Maps.
ICANN 1996: 821-826 |
| 1994 |
| 1 | | Thomas Villmann,
Ralf Der,
J. Michael Herrmann,
Thomas Martinetz:
Topology Preservation in Self-Organizing Feature Maps: General Definition and Efficient Measurement.
Fuzzy Days 1994: 159-166 |