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Memristive Mixed-Signal Neuromorphic Systems: Energy-Efficient Learning at the Circuit-Level.

, , , , , and . IEEE J. Emerg. Sel. Topics Circuits Syst., 8 (1): 125-136 (2018)

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Stochasticity in Neuromorphic Computing: Evaluating Randomness for Improved Performance., , , , and . ICECS, page 454-457. IEEE, (2019)Towards Synaptic Behavior of Nanoscale ReRAM Devices for Neuromorphic Computing Applications., , , , , , , , and . ACM J. Emerg. Technol. Comput. Syst., 16 (2): 23:1-23:18 (2020)A mixed-signal approach to memristive neuromorphic system design., , , and . MWSCAS, page 547-550. IEEE, (2017)A synchronized axon hillock neuron for memristive neuromorphic systems., , and . MWSCAS, page 361-364. IEEE, (2017)A Study of Complex Deep Learning Networks on High-Performance, Neuromorphic, and Quantum Computers., , , , , , , , and . ACM J. Emerg. Technol. Comput. Syst., 14 (2): 19:1-19:21 (2018)Energy and Area Efficiency in Neuromorphic Computing for Resource Constrained Devices., , , , , and . ACM Great Lakes Symposium on VLSI, page 379-383. ACM, (2018)High-Level Simulation for Spiking Neuromorphic Computing Systems., , , , and . ISCAS, page 1-5. IEEE, (2018)A programming framework for neuromorphic systems with emerging technologies., , , , , , and . NANOCOM, page 15:1-15:7. ACM, (2017)Adiabatic Quantum Computation Applied to Deep Learning Networks., , , , , , , , and . Entropy, 20 (5): 380 (2018)A Study of Complex Deep Learning Networks on High Performance, Neuromorphic, and Quantum Computers., , , , , , , , and . MLHPC@SC, page 47-55. IEEE Computer Society, (2016)