Neuromorphic Learning and Recognition With One-Transistor-One-Resistor Synapses and Bistable Metal Oxide RRAM

Resistive switching memory (RRAM) has been proposed as an artificial synapse in neuromorphic circuits due to its tunable resistance, low power operation, and scalability. For the development of high-density neuromorphic circuits, it is essential to validate the state-of-the-art bistable RRAM and to introduce small-area building blocks serving as artificial synapses. This paper introduces a new synaptic circuit consisting of a one-transistor/one-resistor structure, where the resistive element is a HfO2 RRAM with bipolar switching. The spike-timing-dependent plasticity is demonstrated in both the deterministic and stochastic regimes of the RRAM. Finally, a fully connected neuromorphic network is simulated showing online unsupervised pattern learning and recognition for various voltages of the POST spike. The results support bistable RRAM for high-performance artificial synapses in neuromorphic circuits.

[1]  Shimeng Yu,et al.  An Electronic Synapse Device Based on Metal Oxide Resistive Switching Memory for Neuromorphic Computation , 2011, IEEE Transactions on Electron Devices.

[2]  C. Stevens.  Quantal release of neurotransmitter and long-term potentiation , 1993, Cell.

[3]  Simone Balatti,et al.  A 2-transistor/1-resistor artificial synapse capable of communication and stochastic learning in neuromorphic systems , 2015, Front. Neurosci..

[4]  Shimeng Yu,et al.  Stochastic learning in oxide binary synaptic device for neuromorphic computing , 2013, Front. Neurosci..

[5]  Alessandro Calderoni,et al.  Voltage-Controlled Cycling Endurance of HfOx-Based Resistive-Switching Memory , 2015, IEEE Transactions on Electron Devices.

[6]  Chris H. Kim,et al.  A Magnetic Tunnel Junction based True Random Number Generator with conditional perturb and real-time output probability tracking , 2014, 2014 IEEE International Electron Devices Meeting.

[7]  Jiantao Zhou,et al.  Stochastic Memristive Devices for Computing and Neuromorphic Applications , 2013, Nanoscale.

[8]  Chiara Bartolozzi,et al.  Neuromorphic Electronic Circuits for Building Autonomous Cognitive Systems , 2014, Proceedings of the IEEE.

[9]  Alessandro Calderoni,et al.  Statistical Fluctuations in HfOx Resistive-Switching Memory: Part I - Set/Reset Variability , 2014, IEEE Transactions on Electron Devices.

[10]  S. Wang,et al.  Malleability of Spike-Timing-Dependent Plasticity at the CA3–CA1 Synapse , 2006, The Journal of Neuroscience.

[11]  S. Balatti,et al.  Resistive Switching by Voltage-Driven Ion Migration in Bipolar RRAM—Part II: Modeling , 2012, IEEE Transactions on Electron Devices.

[12]  Ya-Chin King,et al.  A Contact-Resistive Random-Access-Memory-Based True Random Number Generator , 2012, IEEE Electron Device Letters.

[13]  B. DeSalvo,et al.  CBRAM devices as binary synapses for low-power stochastic neuromorphic systems: Auditory (Cochlea) and visual (Retina) cognitive processing applications , 2012, 2012 International Electron Devices Meeting.

[14]  D. Ielmini,et al.  Set Variability and Failure Induced by Complementary Switching in Bipolar RRAM , 2013, IEEE Electron Device Letters.

[15]  E. Vianello,et al.  Bio-Inspired Stochastic Computing Using Binary CBRAM Synapses , 2013, IEEE Transactions on Electron Devices.

[16]  Stefano Ambrogio,et al.  True Random Number Generation by Variability of Resistive Switching in Oxide-Based Devices , 2015, IEEE Journal on Emerging and Selected Topics in Circuits and Systems.

[17]  Giacomo Indiveri,et al.  Memory and Information Processing in Neuromorphic Systems , 2015, Proceedings of the IEEE.

[18]  J Joshua Yang,et al.  Memristive devices for computing. , 2013, Nature nanotechnology.

[19]  D. Ielmini,et al.  Complementary Switching in Oxide-Based Bipolar Resistive-Switching Random Memory , 2013, IEEE Transactions on Electron Devices.

[20]  S. Balatti,et al.  Resistive Switching by Voltage-Driven Ion Migration in Bipolar RRAM—Part I: Experimental Study , 2012, IEEE Transactions on Electron Devices.

[21]  P. J. Sjöström,et al.  Rate, Timing, and Cooperativity Jointly Determine Cortical Synaptic Plasticity , 2001, Neuron.

[22]  Shimeng Yu,et al.  Metal–Oxide RRAM , 2012, Proceedings of the IEEE.

[23]  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.

[24]  Masahide Matsumoto,et al.  A 130.7-$\hbox{mm}^{2}$ 2-Layer 32-Gb ReRAM Memory Device in 24-nm Technology , 2014, IEEE Journal of Solid-State Circuits.

[25]  S. Ambrogio,et al.  Analytical Modeling of Oxide-Based Bipolar Resistive Memories and Complementary Resistive Switches , 2014, IEEE Transactions on Electron Devices.

[26]  D. Ielmini,et al.  Modeling the Universal Set/Reset Characteristics of Bipolar RRAM by Field- and Temperature-Driven Filament Growth , 2011, IEEE Transactions on Electron Devices.