Extraction of temporally correlated features from dynamic vision sensors with spike-timing-dependent plasticity
暂无分享,去创建一个
Damien Querlioz | Olivier Bichler | Christian Gamrat | Simon J. Thorpe | Jean-Philippe Bourgoin | S. Thorpe | D. Querlioz | O. Bichler | C. Gamrat | J. Bourgoin
[1] Olivier Bichler,et al. Phase change memory as synapse for ultra-dense neuromorphic systems: Application to complex visual pattern extraction , 2011, 2011 International Electron Devices Meeting.
[2] Bernabé Linares-Barranco,et al. Spike-Based Convolutional Network for Real-Time Processing , 2010, 2010 20th International Conference on Pattern Recognition.
[3] Damien Querlioz,et al. Unsupervised features extraction from asynchronous silicon retina through Spike-Timing-Dependent Plasticity , 2011, The 2011 International Joint Conference on Neural Networks.
[4] Damien Querlioz,et al. Learning with memristive devices: How should we model their behavior? , 2011, 2011 IEEE/ACM International Symposium on Nanoscale Architectures.
[5] Eugene M. Izhikevich,et al. Relating STDP to BCM , 2003, Neural Computation.
[6] Heiko Wersing,et al. Learning Optimized Features for Hierarchical Models of Invariant Object Recognition , 2003, Neural Computation.
[7] Tobi Delbrück,et al. A 128$\times$ 128 120 dB 15 $\mu$s Latency Asynchronous Temporal Contrast Vision Sensor , 2008, IEEE Journal of Solid-State Circuits.
[8] G. Bi,et al. Synaptic Modifications in Cultured Hippocampal Neurons: Dependence on Spike Timing, Synaptic Strength, and Postsynaptic Cell Type , 1998, The Journal of Neuroscience.
[9] Damien Querlioz,et al. Simulation of a memristor-based spiking neural network immune to device variations , 2011, The 2011 International Joint Conference on Neural Networks.
[10] Wolfgang Maass,et al. STDP enables spiking neurons to detect hidden causes of their inputs , 2009, NIPS.
[11] Tobias Delbrück,et al. Frame-free dynamic digital vision , 2008 .
[12] Timothée Masquelier,et al. Competitive STDP-Based Spike Pattern Learning , 2009, Neural Computation.
[13] Kwabena Boahen,et al. Optic nerve signals in a neuromorphic chip II: testing and results , 2004, IEEE Transactions on Biomedical Engineering.
[14] Rufin VanRullen,et al. Temporal codes and sparse representations: A key to understanding rapid processing in the visual system , 2004, Journal of Physiology-Paris.
[15] H. Markram,et al. Regulation of Synaptic Efficacy by Coincidence of Postsynaptic APs and EPSPs , 1997, Science.
[16] Lyle N. Long,et al. Character Recognition using Spiking Neural Networks , 2007, 2007 International Joint Conference on Neural Networks.
[17] W. Lu,et al. High-density crossbar arrays based on a Si memristive system. , 2009, Nano letters.
[18] Y. Dan,et al. Spike Timing-Dependent Plasticity of Neural Circuits , 2004, Neuron.
[19] Sander M. Bohte,et al. Reducing the Variability of Neural Responses: A Computational Theory of Spike-Timing-Dependent Plasticity , 2007, Neural Computation.
[20] Timothée Masquelier,et al. Unsupervised Learning of Visual Features through Spike Timing Dependent Plasticity , 2007, PLoS Comput. Biol..
[21] S. Thorpe,et al. Spike Timing Dependent Plasticity Finds the Start of Repeating Patterns in Continuous Spike Trains , 2008, PloS one.
[22] Kwabena Boahen,et al. Optic nerve signals in a neuromorphic chip I: Outer and inner retina models , 2004, IEEE Transactions on Biomedical Engineering.
[23] Wulfram Gerstner,et al. Emergence of spatiotemporal receptive fields and its application to motion detection , 1994, Biological Cybernetics.