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Legenstein, R., H. Markram, and W. Maass, "Input prediction and autonomous movement analysis in recurrent circuits of spiking neurons", Reviews in the Neurosciences (Special Issue on Neuroinformatics of Neural and Artificial Computation), vol. 14, no. 1-2, pp. 5-19, 2003. Abstract
Li, J., and H. Jaeger, "Minimal Energy Control of an ESN Pattern Generator", Jacobs University Technical Report, no. 26: Jacobs University Bremen, 2011. Abstract
Lukoševičius, M., Echo state networks with trained feedbacks, , no. 4: Jacobs University Bremen, February, 2007.
Lukoševičius, M., "A practical guide to applying echo state networks", Neural Networks: Tricks of the Trade, 2, vol. 7700: Springer Berlin Heidelberg, pp. 659-686, 2012.  Download: PracticalESN.pdf (624.47 KB)
Lukoševičius, M., and V. Marozas, "Noninvasive Fetal QRS Detection using Echo State Network", Computing in Cardiology 2013, vol. 40, Zaragoza, Spain, pp. 205-208, 2013.  Download: FQRS_ESN.pdf (252.39 KB)
Lukoševičius, M., and H. Jaeger, "Reservoir computing approaches to recurrent neural network training", Computer Science Review , vol. 3, no. 3, pp. 127-149, August, 2009.
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)
Lukoševičius, M., "Reservoir Computing and Self-Organized Neural Hierarchies", School of Engineering and Science, vol. PhD: Jacobs University Bremen, 2012. Abstract  Download: Mantas_Lukosevicius_PhD_thesis.pdf (3.13 MB)
Lukoševičius, M., H. Jaeger, and B. Schrauwen, "Reservoir Computing Trends", KI - Künstliche Intelligenz, pp. 1-7, 05/2012. Abstract  Download: KI_reservoir_computing.pdf (574.71 KB)
Maass, W., R. Legenstein, and H. Markram, "A new approach towards vision suggested by biologically realistic neural microcircuit models", Biologically Motivated Computer Vision BMCV 2002, vol. 2525: Springer, pp. 282-293, 2002. Abstract
Maass, W., and H. Markram, "On the computational power of recurrent circuits of spiking neurons", Journal of Computer and System Sciences, vol. 69, no. 4, pp. 593-616, 2004. Abstract
Maass, W., "Computing with spikes", Special Issue on Foundations of Information Processing of Telematik, vol. 8, no. 1, pp. 32-36, 2002.
Maass, W., "Motivation, theory, and applications of liquid state machines", Computability in Context: Computation and Logic in the Real World: Imperial College Press, 2011. Abstract
Maass, W., R. Legenstein, and N. Bertschinger, "Methods for estimating the computational power and generalization capability of neural microcircuits", NIPS 2004: Advances in Neural Information Processing Systems, vol. 17: MIT Press, pp. 865-872, 2005, 2004. Abstract
Maass, W., and H. Markram, "Temporal integration in recurrent microcircuits", The Handbook of Brain Theory and Neural Networks, 2nd Edition: MIT Press, pp. 1159-1163, 2003.