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Realizing Green Symbol Detection via Reservoir Computing: An Energy-Efficiency Perspective.

, , , , , , и . ICC, стр. 1-6. IEEE, (2018)

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Jennifer Bryant

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Szczepan Wysocki

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Energy Efficient Spiking Temporal Encoder Design for Neuromorphic Computing Systems., , , , , , и . IEEE Trans. Multi Scale Comput. Syst., 2 (4): 265-276 (2016)Hardware-Based Computational Intelligence for Size, Weight, and Power Constrained Environments., , , , и . Network Science and Cybersecurity, том 55 из Advances in Information Security, Springer, (2014)Nanoelectronics and Hardware Security., , , , , и . Network Science and Cybersecurity, том 55 из Advances in Information Security, Springer, (2014)Neuromorphic encoding system design with chaos based CMOS analog neuron., , , и . CISDA, стр. 1-6. IEEE, (2015)Nanoelectronic Solutions for Hardware Security., , , , , , и . IACR Cryptol. ePrint Arch., (2012)Compact method for modeling and simulation of memristor devices: Ion conductor chalcogenide-based memristor devices., , , , , , , и . NANOARCH, стр. 1-4. IEEE Computer Society, (2010)Analysis of dynamic linear and non-linear memristor device models for emerging neuromorphic computing hardware design., , , и . IJCNN, стр. 1-5. IEEE, (2010)Channel estimation in wireless OFDM systems using reservoir computing., , , , , и . CISDA, стр. 1-5. IEEE, (2015)Stochastic CBRAM-Based Neuromorphic Time Series Prediction System., , , и . JETC, 13 (3): 37:1-37:14 (2017)Spike-Time-Dependent Encoding for Neuromorphic Processors., , , , , и . JETC, 12 (3): 23:1-23:21 (2015)