Dynamical complexity and computation in recurrent neural networks beyond their fixed point
暂无分享,去创建一个
D. Brunner | L. Larger | Y. Chembo | B. Marquez | M. Jacquot
[1] Fredric M. Wolf,et al. Random Wiring, Ganglion Cell Mosaics, and the Functional Architecture of the Visual Cortex , 2015, PLoS Comput. Biol..
[2] Louis M Pecora,et al. Synchronization of chaotic systems. , 2015, Chaos.
[3] H Sompolinsky,et al. Dynamics of random neural networks with bistable units. , 2014, Physical review. E, Statistical, nonlinear, and soft matter physics.
[4] H. Sompolinsky,et al. Sparseness and Expansion in Sensory Representations , 2014, Neuron.
[5] Sitabhra Sinha,et al. Complex patterns arise through spontaneous symmetry breaking in dense homogeneous networks of neural oscillators , 2013, Scientific Reports.
[6] L. Abbott,et al. Random Convergence of Olfactory Inputs in the Drosophila Mushroom Body , 2013, Nature.
[7] G. Wainrib,et al. Topological and dynamical complexity of random neural networks. , 2012, Physical review letters.
[8] H. Sompolinsky,et al. Compressed sensing, sparsity, and dimensionality in neuronal information processing and data analysis. , 2012, Annual review of neuroscience.
[9] L Pesquera,et al. Photonic information processing beyond Turing: an optoelectronic implementation of reservoir computing. , 2012, Optics express.
[10] Benjamin Schrauwen,et al. Optoelectronic Reservoir Computing , 2011, Scientific Reports.
[11] J. Fell,et al. The role of phase synchronization in memory processes , 2011, Nature Reviews Neuroscience.
[12] Olaf Sporns,et al. The Non-Random Brain: Efficiency, Economy, and Complex Dynamics , 2010, Front. Comput. Neurosci..
[13] Mehdi Khamassi,et al. Coherent Theta Oscillations and Reorganization of Spike Timing in the Hippocampal- Prefrontal Network upon Learning , 2010, Neuron.
[14] L. F. Abbott,et al. Generating Coherent Patterns of Activity from Chaotic Neural Networks , 2009, Neuron.
[15] S. Marco,et al. Biologically Inspired Signal Processing for Chemical Sensing , 2009 .
[16] Michael Elad,et al. From Sparse Solutions of Systems of Equations to Sparse Modeling of Signals and Images , 2009, SIAM Rev..
[17] Nikolai Axmacher,et al. Phase-locking within human mediotemporal lobe predicts memory formation , 2008, NeuroImage.
[18] Du Qu Wei,et al. Ordering spatiotemporal chaos in discrete neural networks with small-world connections , 2007 .
[19] Robert A. Legenstein,et al. At the Edge of Chaos: Real-time Computations and Self-Organized Criticality in Recurrent Neural Networks , 2004, NIPS.
[20] Nils Bertschinger,et al. Real-Time Computation at the Edge of Chaos in Recurrent Neural Networks , 2004, Neural Computation.
[21] Harald Haas,et al. Harnessing Nonlinearity: Predicting Chaotic Systems and Saving Energy in Wireless Communication , 2004, Science.
[22] D. Debanne,et al. Long-term plasticity of intrinsic excitability: learning rules and mechanisms. , 2003, Learning & memory.
[23] Sanjoy Dasgupta,et al. An elementary proof of a theorem of Johnson and Lindenstrauss , 2003, Random Struct. Algorithms.
[24] C. Gray,et al. Dynamic spike threshold reveals a mechanism for synaptic coincidence detection in cortical neurons in vivo. , 2000, Proceedings of the National Academy of Sciences of the United States of America.
[25] P Rappelsberger,et al. Long-range EEG synchronization during word encoding correlates with successful memory performance. , 2000, Brain research. Cognitive brain research.
[26] Christoph Braun,et al. Coherence of gamma-band EEG activity as a basis for associative learning , 1999, Nature.
[27] Piotr Indyk,et al. Approximate nearest neighbors: towards removing the curse of dimensionality , 1998, STOC '98.
[28] W. Singer,et al. Integrator or coincidence detector? The role of the cortical neuron revisited , 1996, Trends in Neurosciences.
[29] M. Rosenstein,et al. A practical method for calculating largest Lyapunov exponents from small data sets , 1993 .
[30] Christopher G. Langton,et al. Computation at the edge of chaos: Phase transitions and emergent computation , 1990 .
[31] Sommers,et al. Chaos in random neural networks. , 1988, Physical review letters.
[32] Farmer,et al. Predicting chaotic time series. , 1987, Physical review letters.
[33] L. Glass,et al. Oscillation and chaos in physiological control systems. , 1977, Science.
[34] C. E. SHANNON,et al. A mathematical theory of communication , 1948, MOCO.
[35] Sang Joon Kim,et al. A Mathematical Theory of Communication , 2006 .
[36] H. Kantz,et al. Nonlinear time series analysis , 1997 .
[37] Ronald J. MacGregor,et al. Neural and brain modeling , 1987 .
[38] Yasuji Sawada,et al. Practical Methods of Measuring the Generalized Dimension and the Largest Lyapunov Exponent in High Dimensional Chaotic Systems , 1987 .
[39] F. Takens. Detecting strange attractors in turbulence , 1981 .
[40] E M Harth,et al. Brain functions and neural dynamics. , 1970, Journal of theoretical biology.