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InProceedings


Bießmann, F., Murayama, Y., Logothetis, N.K., Müller, K.R., and Meinecke, F.C. (2011). Non-Separable Spatiotemporal Deconvolutions Improve Decoding of Neural Activity from fMRI Signals. NIPS Workshop "Machine Learning and Interpretation in Neuroimaging"


Bießmann, F., and Harth, A. (2010). Analysing Dependency Dynamics in Web Data. Proceedings of AAAI Spring Symposium "Linked Data Meets Artificial Intelligence"


Antons, J.-N., Schleicher, R., Wolf, I., Porbadnigk, A.K., Blankertz, B., Möller, S., and Curio, G. (2010). Neural Correlates of Speech Degradation – Subjective Ratings and Brain Activation in Case of Signal-correlated Noise. In Proc. of the 3rd Int’l Workshop on Perceptual Quality of Systems


2

Hahne, J.M., Rehbaum, H., Bießmann, F., Meinecke, F.C., Müller, K.-R., Jiang, N., Farina, D., and Parra, L.C. (2012). Simultaneous and proportional control of 2D wrist movements with myoelectric signals.. 2012 IEEE International Workshop on Machine Learning for Signal Processing


Rost, T., Ramachandran, H., Nawrot, M.P., and Chicca, E. (2013). A neuromorphic approach to auditory pattern recognition in cricket phonotaxis. 21st European Conference on Cricuit Theory and Design (in press)


4

Natora, M., Franke, F., Broda, S., and Obermayer, K. (2010). Optimal Steering Vector Adaptation for Linear Filters Leading to Robust Beamforming. 4th International Symposium on Communications, Control and Signal Processing, Cyprus


A

Hill, J., Farquhar, J., Martens, S.M.M., Bießmann, F., and Schölkopf, B. (2008). Effects of Stimulus Type and of Error-Correcting Code Design on BCI Speller Performance. Advances in Neural Information Processing Systems, 665-673.


Dähne, S., Höhne, J., Schreuder, M., and Tangermann, M. (2011). Slow feature analysis - A tool for extraction of discriminating event-related potentials in brain-computer interfaces. Artificial Neural Networks and Machine Learning ICANN, 36-43.


B

Helgadottir, L.I., Haenicke, J., Landgraf, T., and Nawrot, M.P. (2012). A robotic platform for spiking neural control architectures. Bernstein Conference proceedings [F128]


Haenicke, J., Pamir, E., and Nawrot, M.P. (2012). A spiking neuronal network model of fast associative learning in the honeybee. Bernstein Conference proceedings [F95]


D'Albis, T., Haenicke, J., Strube-Bloss, M.F., Schmuker, M., Menzel, R., and Nawrot, M.P. (2011). Learning-induced changes at the single neuron level predict behavioral performance in the honeybee. Bernstein Conference proceedings [T24]


Meyer, J., Haenicke, J., Landgraf, T., Schmuker, M., Rojas, R., and Nawrot, M.P. (2011). A digital receptor neuron connecting remote sensor hardware to spiking neural networks. Bernstein Conference proceedings [W84]


Roemschied, F.A., Ronacher, B., Eberhard, M.J., and Schreiber, S. (2011). Temperature Differentially Affects Subsequent Layers of Auditory Neurons in the Locust. Computational Neuroscience Meeting, Stockholm, Sweden, P287.


C

Porbadnigk, A., Antons, J.N., Blankertz, B., Tredes, M.S., Schleicher, R., Möller, S., and Curio, G. (2010). Using ERPs for assessing the (sub)conscious perception of noise. Conference Proceedings IEEE Engineering in Medicine and Biology Society, 2690-2693.


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