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Natschläger, T., W. Maass, and H. Markram, "The "Liquid Computer": A Novel Strategy for Real-Time Computing on Time Series", Special Issue on Foundations of Information Processing of {TELEMATIK}, vol. 8, no. 1, pp. 39–43, 2002. Abstract
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Tong, M. H., A. D. Bickett, E. M. Christiansen, and G. W. Cottrell, "2007 Special Issue: Learning grammatical structure with Echo State Networks", Neural Networks, vol. 20, no. 3, Oxford, UK, UK, Elsevier Science Ltd., pp. 424–432, 2007.
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Jaeger, H., Adaptive nonlinear system identification with echo state networks, : MIT Press Cambridge, MA, pp. 593–600, 2003.
Jaeger, H., "Adaptive nonlinear system identification with echo state networks", In: Advances in Neural Information Processing Systems: MIT Press, Cambridge, MA, , pp. 593-600, 2003, 2002.
Strauß, T., "Alternative Konvergenzmaße für die Beschreibung des Verhaltens von Echo - State - Netzen", insitute for mathematics, vol. Diploma, Rostock, University of Rostock, pp. 68, 05/2009. Abstract  Download: Diplomarbeit T. Strauß.pdf (1.35 MB)
Dominey, P. F., J. Ventre-Dominey, E. Broussolle, and M. Jeannerod, "Analogical transfer in sequence learning. Human and neural-network models of frontostriatal function", Annals of the New York Academy of Sciences, vol. 769, pp. 369-73 , 1995. Abstract
Dominey, P. F., J. Ventre-Dominey, E. Broussolle, and M. Jeannerod, "Analogical transfer is effective in a serial reaction time task in Parkinson's disease: evidence for a dissociable form of sequence learning", Neuropsychologia, vol. 35, no. 1, pp. 1-9, 1997. Abstract
Ozturk, M. C., D. Xu, and J. C. Principe, "Analysis and Design of Echo State Networks", Neural Computation, vol. 19, pp. 111–138, 2006.
Schiller, U. D., and J. J. Steil, "Analyzing the weight dynamics of recurrent learning algorithms", Neurocomputing, vol. 63C, pp. 5-23, 2005.
Dominey, P. F., "An anatomically structured sensory-motor sequence learning system displays some general linguistic capacities.", Brain and Language, vol. 59, no. 1, pp. 50-75, 1997. Abstract  Download: dominey1997brainlang.pdf (198.49 KB)
Skowronski, M. D., and J. G. Harris, "Automatic speech recognition using a predictive echo state network classifier", Neural Networks, vol. 20, no. 3: Elsevier Science Ltd. Oxford, UK, UK, pp. 414–423, 2007.
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Steil, J. J., "Backpropagation-Decorrelation: online recurrent learning with O(N) complexity,", IJCNN, 2004.
wyffels, F., B. Schrauwen, D. Verstraeten, and D. Stroobandt, "Band-pass reservoir computing", Proceedings of the International Joint Conference on Neural Networks, Hong Kong, pp. 3203-3208, 6, 2008.
Steimer, A., W. Maass, and R. Douglas, "Belief-propagation in networks of spiking neurons", Neural Computation, vol. 21, pp. 2502-2523, 2009. Abstract
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Jaeger, H., and D. Eck, "Can't Get You Out of My Head: A Connectionist Model of Cyclic Rehearsal. ", In: I. Wachsmuth, G. Knoblich (eds.): Modeling Communication for Robots and Virtual Humans. : Springer LNAI 4930, pp. 310-335 , 2008.
Yamazaki, T., and S. Tanaka, "The cerebellum as a liquid state machine", Neural Networks, vol. 20, pp. 290-297, 2007.
Lelekov, T., N. Franck, P. F. Dominey, and N. Georgieff, "Cognitive sequence processing and syntactic comprehension in schizophrenia", NeuroReport, vol. 11, no. 10, pp. 2145-9, 07/2000. Abstract
Jouen, A-L., T. M. Ellmore, C. Madden, C. Pallier, P. F. Dominey, and J. Ventre-Dominey, "A common “meaning” system for language and visual images revealed by fMRI and DTI", Society for Neuroscience, 2011. Abstract
Schrauwen, B., M. D'Haene, D. Verstraeten, and J. Van Campenhout, "Compact hardware for real-time speech recognition using a Liquid State Machine", Proceedings of the International Joint Conference on Neural Networks (IJCNN), 2007.
Daukantas, S., M. Lukoševičius, V. Marozas, and A. Lukoševičius, "Comparison of ``black box'' and ``gray box'' methods for lost data reconstruction in multichannel signals", Proceedings of the 14th International Conference ``Biomedical Engineering'', Kaunas, pp. 135-138, 2010.
Dominey, P. F., "Complex sensory-motor sequence learning based on recurrent state representation and reinforcement learning", Biological Cybernetics, vol. 73, no. 3, pp. 265-74, 08/1995.  Download: dominey1995biocyber.pdf (996.6 KB)
Maass, W., P. Joshi, and E. D. Sontag, "Computational aspects of feedback in neural circuits", PLoS Computational Biology, vol. 3, no. 1, pp. 1-20, 2007. Abstract
Maass, W., T. Natschläger, and H. Markram, "Computational models for generic cortical microcircuits", Computational Neuroscience: A Comprehensive Approach: CRC-Press, 2004. Abstract
Natschläger, T., H. Markram, and W. Maass, "Computer models and analysis tools for neural microcircuits", A Practical Guide to Neuroscience Databases and Associated Tools: Kluver Academic Publishers (Boston), 2002.
Natschlaeger, T., H. Markram, and W. Maass, "Computer Models and analysis tools for neural microcircuits", Neuroscience Databases. A Practical Guide, Boston, Kluwer Academic Publishers, pp. 123-138, 2003. Abstract