Publications

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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.
Schürmann, F., K. Meier, and J. Schemmel, "Edge of Chaos Computation in Mixed-Mode {VLSI} - ``{A} Hard Liquid''", Advances in Neural Information Processing Systems 17, Cambridge, MA, MIT Press, pp. 1201-1208, 2005.
Siewert, U., and W. Wustlich, Echo-State Networks with Band-Pass Neurons: Towards Generic Time-Scale-Independent Reservoir Structures, , Raben-Steinfeld, Germany, Planet intelligent systems GmbH, October, 2007.
Skowronski, M. D., and J. G. Harris, "Minimum mean squared error time series classification using an echo state network prediction model", IEEE International Symposium on Circuits and Systems, 2006.
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.
Skowronski, M. D., and J. G. Harris, "Noise-Robust Automatic Speech Recognition Using a Predictive Echo State Network", Audio, Speech and Language Processing, IEEE Transactions on [see also Speech and Audio Processing, IEEE Transactions on], vol. 15, no. 5, pp. 1724–1730, 2007.
Steil, J. J., "Online Reservoir Adaptation by Intrinsic Plasticity for Backpropagation-Decorrelation and Echo State Learning", Neural Networks, vol. 20, no. 3, pp. 353 - 364, 2007.
Steil, J. J., "Backpropagation-Decorrelation: online recurrent learning with O(N) complexity,", IJCNN, 2004.
Steimer, A., W. Maass, and R. Douglas, "Belief-propagation in networks of spiking neurons", Neural Computation, vol. 21, pp. 2502-2523, 2009. Abstract
Stouten, F., J. Duchateau, J-P. Martens, and P. Wambacq, Coping with disfluencies in Spontaneous Speech Recognition: acoustic detection and linguistic context manipulation, , 2006.
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)
Sussillo, D., and L. D. Abbott, "Generating Coherent Patterns of Activity from Chaotic Neural Networks", Neuron, vol. 63, pp. 544 - 557, 2009. 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.
Triefenbach, F., A. Jalalvand, B. Schrauwen, and J-P. Martens, "Phoneme Recognition with Large Hierarchical Reservoirs", Neural Information Processing Systems (NIPS2010) , 2010. Abstract  Download: ftriefen_nips2010.pdf (782.18 KB)
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Verstraeten, D., B. Schrauwen, D. Stroobandt, and J. Van Campenhout, "Isolated word recognition with the Liquid State Machine: a case study", Information Processing Letters, vol. 95, no. 6, pp. 521–528, 2005.
Verstraeten, D., Een studie van de {L}iquid {S}tate {M}achine: een woordherkenner, : Ghent University, ELIS department, 2004.
Verstraeten, D., B. Schrauwen, and J V. Campenhout, "Recognition of Isolated Digits using a Liquid State Machine", Proceedings of SPS-DARTS 2005, pp. 135–138, April, 2005.
Verstraeten, D., B. Schrauwen, and D. Stroobandt, "Reservoir-based techniques for speech recognition", Proceedings of the World Conference on Computational Intelligence, pp. 1050-1053, 2006.
Verstraeten, D., B. Schrauwen, S. Dieleman, P. Brakel, P. Buteneers, and D. Pecevski, "Oger: Modular Learning Architectures For Large-Scale Sequential Processing", Journal of Machine Learning Research, Submitted.  Download: Verstraeten11.pdf (186.23 KB)
Verstraeten, D., B. Schrauwen, and D. Stroobandt, "Isolated word recognition using a Liquid State Machine", Proceedings of the 13th European Symposium on Artificial Neural Networks (ESANN), Evere, D-side Publications, pp. 435–440, May, 2005.
Verstraeten, D., "Reservoir Computing: computation with dynamical systems", Electronics and Information Systems, Gent, Ghent University, pp. 190, 2009.  Download: dvrstrae_organic.pdf (7.23 MB)
Vreeken, J., On real-world temporal pattern recognition using Liquid State Machines, : Institute for Information and Computing Sciences, Utrecht University, Submitted.
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Waegeman, T., E. Antonelo, F. wyffels, and B. Schrauwen, "Modular reservoir computing networks for imitation learning of multiple robot behaviors", Proc. of the IEEE Int. Symp. on Computational Intelligence in Robotics and Automation (CIRA), 2009.  Download: p27.pdf (2.34 MB)
wyffels, F., B. Schrauwen, and D. Stroobandt, "Stable output feedback in reservoir computing using ridge regression", International Conference on Artificial Neural Networks, 2008.
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.