Tunnel junction based memristors as artificial synapses
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Elisabetta Chicca | Andy Thomas | Joachim Wollschläger | Olga Kuschel | Patryk Krzysteczko | A. Thomas | P. Krzysteczko | E. Chicca | K. Küpper | J. Wollschläger | Stefan Niehörster | Savio Fabretti | Norman Shepheard | Karsten Küpper | Stefan Niehörster | Savio Fabretti | N. Shepheard | O. Kuschel | Andy Thomas
[1] A. Hippel. Ferroelectricity, Domain Structure, and Phase Transitions of Barium Titanate , 1950 .
[2] W. E. Beadle,et al. Switching properties of thin Nio films , 1964 .
[3] W. Brinkman,et al. Tunneling Conductance of Asymmetrical Barriers , 1970 .
[4] Yoshihiro Ishibashi,et al. Note on Ferroelectric Domain Switching , 1971 .
[5] M. Julliere. Tunneling between ferromagnetic films , 1975 .
[6] G. M. Rose,et al. Induction of hippocampal long-term potentiation using physiologically patterned stimulation , 1986, Neuroscience Letters.
[7] Carver Mead,et al. Analog VLSI and neural systems , 1989 .
[8] S. Tam,et al. An electrically trainable artificial neural network (ETANN) with 10240 'floating gate' synapses , 1990, International 1989 Joint Conference on Neural Networks.
[9] Carver A. Mead,et al. Neuromorphic electronic systems , 1990, Proc. IEEE.
[10] J. Brant Arseneau,et al. VLSI and neural systems , 1990 .
[11] Sung Wook Park,et al. Effects of oxidation conditions on the properties of tantalum oxide films on silicon substrates , 1992 .
[12] Yoshihiro Ishibashi,et al. Study on D-E Hysteresis Loop of TGS Based on the Avrami-Type Model , 1994 .
[13] Sang-Sub Kim,et al. Structural characterization of epitaxial BaTiO3 thin films grown by sputter deposition on MgO(100) , 1995 .
[14] I. Chen,et al. Fatigue of Pb(Zr0.53Ti0.47)O3 ferroelectric thin films , 1998 .
[15] 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.
[16] Jagadeesh S. Moodera,et al. Spin polarized tunneling in ferromagnetic junctions , 1999 .
[17] Davide Badoni,et al. Spike-Driven Synaptic Plasticity: Theory, Simulation, VLSI Implementation , 2000, Neural Computation.
[18] M. Hehn,et al. Tantalum oxide as an alternative low height tunnel barrier in magnetic junctions , 2001 .
[19] J. Gilman,et al. Nanotechnology , 2001 .
[20] Paul E. Hasler,et al. Biological learning modeled in an adaptive floating-gate system , 2002, 2002 IEEE International Symposium on Circuits and Systems. Proceedings (Cat. No.02CH37353).
[21] A. Tagantsev,et al. Non-Kolmogorov-Avrami switching kinetics in ferroelectric thin films , 2002 .
[22] H. Kubota,et al. Size dependence of switching field of magnetic tunnel junctions down to 50 nm scale , 2003 .
[23] Thomas Mikolajick,et al. Material Aspects in Emerging Nonvolatile Memories , 2004 .
[24] G. Reiss,et al. Aluminum oxidation by a remote electron cyclotron resonance plasma in magnetic tunnel junctions , 2003 .
[25] Vittorio Dante,et al. A VLSI recurrent network of integrate-and-fire neurons connected by plastic synapses with long-term memory , 2003, IEEE Trans. Neural Networks.
[26] Y. Huai,et al. Observation of spin-transfer switching in deep submicron-sized and low-resistance magnetic tunnel junctions , 2004, cond-mat/0504486.
[27] M. Fiebig. Revival of the magnetoelectric effect , 2005 .
[28] E. Tsymbal,et al. Applied physics. Tunneling across a ferroelectric. , 2006, Science.
[29] R. Waser,et al. Nanoionics-based resistive switching memories. , 2007, Nature materials.
[30] Gert Cauwenberghs,et al. Dynamically Reconfigurable Silicon Array of Spiking Neurons With Conductance-Based Synapses , 2007, IEEE Transactions on Neural Networks.
[31] Walter Senn,et al. Learning Real-World Stimuli in a Neural Network with Spike-Driven Synaptic Dynamics , 2007, Neural Computation.
[32] Jiyoung Kim,et al. Random and localized resistive switching observation in Pt/NiO/Pt , 2007 .
[33] Xinman Chen,et al. Resistive switching behavior of Pt/Mg0.2Zn0.8O/Pt devices for nonvolatile memory applications , 2008 .
[34] D. Stewart,et al. The missing memristor found , 2008, Nature.
[35] S. Takahashi,et al. Lower-current and fast switching of a perpendicular TMR for high speed and high density spin-transfer-torque MRAM , 2008, 2008 IEEE International Electron Devices Meeting.
[36] G. Reiss,et al. Direct imaging of the structural change generated by dielectric breakdown in MgO based magnetic tunnel junctions , 2008, 0806.2028.
[37] H. N. Lee,et al. Nonlinear dynamics of domain-wall propagation in epitaxial ferroelectric thin films. , 2009, Physical review letters.
[38] Mario Pannunzi,et al. Classification of Correlated Patterns with a Configurable Analog VLSI Neural Network of Spiking Neurons and Self-Regulating Plastic Synapses , 2009, Neural Computation.
[39] Warren Robinett,et al. Memristor-CMOS hybrid integrated circuits for reconfigurable logic. , 2009, Nano letters.
[40] Giacomo Indiveri,et al. Real-Time Classification of Complex Patterns Using Spike-Based Learning in Neuromorphic VLSI , 2009, IEEE Transactions on Biomedical Circuits and Systems.
[41] Wei Wu,et al. A hybrid nanomemristor/transistor logic circuit capable of self-programming , 2009, Proceedings of the National Academy of Sciences.
[42] Andy Thomas,et al. Current induced resistance change of magnetic tunnel junctions with ultra-thin MgO tunnel barriers , 2008, 0807.4422.
[43] V. Garcia,et al. Giant tunnel electroresistance for non-destructive readout of ferroelectric states , 2009, Nature.
[44] G. Reiss,et al. Electric breakdown in ultrathin MgO tunnel barrier junctions for spin-transfer torque switching , 2009, 0907.3579.
[45] R. Dittmann,et al. Redox‐Based Resistive Switching Memories – Nanoionic Mechanisms, Prospects, and Challenges , 2009, Advanced materials.
[46] P. Krzysteczko,et al. Memristive switching of MgO based magnetic tunnel junctions , 2009, 0907.3684.
[47] Ralph Etienne-Cummings,et al. A CMOS switched capacitor implementation of the Mihalas-Niebur neuron , 2009, 2009 IEEE Biomedical Circuits and Systems Conference.
[48] Bernabé Linares-Barranco,et al. Memristance can explain Spike-Time-Dependent-Plasticity in Neural Synapses , 2009 .
[49] Wei Yang Lu,et al. Nanoscale memristor device as synapse in neuromorphic systems. , 2010, Nano letters.
[50] Rainer Waser,et al. Complementary resistive switches for passive nanocrossbar memories. , 2010, Nature materials.
[51] Paul E. Hasler,et al. Floating gate synapses with spike time dependent plasticity , 2010, Proceedings of 2010 IEEE International Symposium on Circuits and Systems.
[52] Gregory S. Snider,et al. ‘Memristive’ switches enable ‘stateful’ logic operations via material implication , 2010, Nature.
[53] P Fons,et al. Interfacial phase-change memory. , 2011, Nature nanotechnology.
[54] R. Williams,et al. Sub-nanosecond switching of a tantalum oxide memristor , 2011, Nanotechnology.
[55] Shubha Ramakrishnan,et al. Floating Gate Synapses With , 2011 .
[56] A. Thomas,et al. Improved reliability of magnetic field programmable gate arrays through the use of memristive tunnel junctions , 2011 .
[57] Hao Yan,et al. Programmable nanowire circuits for nanoprocessors , 2011, Nature.
[58] M. Kozicki,et al. Electrochemical metallization memories—fundamentals, applications, prospects , 2011, Nanotechnology.
[59] Yuriy V. Pershin,et al. Memory effects in complex materials and nanoscale systems , 2010, 1011.3053.
[60] Kinam Kim,et al. A fast, high-endurance and scalable non-volatile memory device made from asymmetric Ta2O(5-x)/TaO(2-x) bilayer structures. , 2011, Nature materials.
[61] J. Grollier,et al. A ferroelectric memristor. , 2012, Nature materials.
[62] A. Thomas,et al. The Memristive Magnetic Tunnel Junction as a Nanoscopic Synapse‐Neuron System , 2012, Advanced materials.
[63] Byoungil Lee,et al. Nanoelectronic programmable synapses based on phase change materials for brain-inspired computing. , 2012, Nano letters.
[64] Paul E. Hasler,et al. STDP-enabled learning on a reconfigurable neuromorphic platform , 2013, 2013 European Conference on Circuit Theory and Design (ECCTD).
[65] A. Thomas,et al. Memristor-based neural networks , 2013 .
[66] Giacomo Indiveri,et al. Integration of nanoscale memristor synapses in neuromorphic computing architectures , 2013, Nanotechnology.
[67] Chung Lam,et al. Brain-like associative learning using a nanoscale non-volatile phase change synaptic device array , 2014, Front. Neurosci..
[68] T. Mikolajick,et al. Exploiting Memristive BiFeO3 Bilayer Structures for Compact Sequential Logics , 2014 .
[69] Leon O. Chua,et al. If it’s pinched it’s a memristor , 2014 .
[70] Chiara Bartolozzi,et al. Neuromorphic Electronic Circuits for Building Autonomous Cognitive Systems , 2014, Proceedings of the IEEE.
[71] F. Zeng,et al. Recent progress in resistive random access memories: Materials, switching mechanisms, and performance , 2014 .
[72] René Schüffny,et al. Switched-capacitor realization of presynaptic short-term-plasticity and stop-learning synapses in 28 nm CMOS , 2014, Front. Neurosci..
[73] Farnood Merrikh-Bayat,et al. Training and operation of an integrated neuromorphic network based on metal-oxide memristors , 2014, Nature.