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Lukoševičius, M., "Self-organized reservoirs and their hierarchies", Proceedings of the 22nd International Conference on Artificial Neural Networks (ICANN 2012), vol. 7553, Lausanne, Switzerland, Springer, pp. 587-595, 2012.  Download: Self-organized_reservoir_hierarchies_ICANN12.pdf (315.2 KB)
Basterrech, S., C. Fyfe, and G. Rubino, "Self-Organizing Maps and Scale-Invariant Maps in Echo State Networks", Intelligent Systems Design and Applications (ISDA), 2011 11th International Conference on, pp. 94 -99, nov., 2011.
Dominey, P. F., "A shared system for learning serial and temporal structure of sensori-motor sequences? Evidence from simulation and human experiments", Cognitive Brain Research, vol. 6, no. 3, pp. 163-172, 01/1998.  Download: dominey 98 cogn brain res.pdf (501.91 KB)
Fette, G., and J. Eggert, "Short Term Memory and Pattern Matching with Simple Echo State Networks", Artificial Neural Networks: Biological Inspirations - ICANN 2005, pp. 13–18, 2005.
Jaeger, H., "Short term memory in echo state networks", GMD Report 152: German National Research Center for Information Technology, 2001.
Buesing, L., and W. Maass, "Simplified rules and theoretical analysis for information bottleneck optimization and PCA with spiking neurons", NIPS 2007: Advances in Neural Information Processing Systems, vol. 20: MIT Press, 2008, 2007. Abstract
, "Special Issue on {Echo State Networks and Liquid State Machines}", Neural Networks, vol. 20, no. 3, 2007.
Buesing, L., and W. Maass, "A spiking neuron as information bottleneck", Neural Computation, vol. 22, 2010. Abstract
Klampfl, S., R. Legenstein, and W. Maass, "Spiking neurons can learn to solve information bottleneck problems and to extract independent components", Neural Computation, vol. 21, no. 4, pp. 911-959, 2009. Abstract
Defour, J., Spraakherkenning met reservoir computing, : Universiteit Gent, 2006.
wyffels, F., B. Schrauwen, and D. Stroobandt, "Stable output feedback in reservoir computing using ridge regression", International Conference on Artificial Neural Networks, 2008.
Buonomano, D., and W. Maass, "State-dependent computations: Spatiotemporal processing in cortical networks", Nature Reviews Neuroscience, vol. 10, no. 2, pp. 113-125, 2009. Abstract
Haeusler, S., and W. Maass, "A statistical analysis of information processing properties of lamina-specific cortical microcircuit models", Cerebral Cortex, vol. 17, no. 1, pp. 149-162, 2007. Abstract
Nessler, B., M. Pfeiffer, and W. Maass, "STDP enables spiking neurons to detect hidden causes of their inputs", NIPS 2009: Advances in Neural Information Processing Systems, vol. 22: MIT Press, 2010, 2009. Abstract
Frank, S. L., "Strong Systematicity in Sentence Processing by an Echo State Network", Proceedings of the International Conference on Artificial Neural Networks, 2006.
Antonelo, E. A., and B. Schrauwen, "Supervised Learning of Internal Models for Autonomous Goal-oriented Robot Navigation using Reservoir Computing", IEEE International Conference on Robotics and Automation (ICRA), 2009.  Download: icra2010_eric.pdf (1.46 MB)