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      Training and operation of an integrated neuromorphic network based on metal-oxide memristors

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          Nanoscale memristor device as synapse in neuromorphic systems.

          A memristor is a two-terminal electronic device whose conductance can be precisely modulated by charge or flux through it. Here we experimentally demonstrate a nanoscale silicon-based memristor device and show that a hybrid system composed of complementary metal-oxide semiconductor neurons and memristor synapses can support important synaptic functions such as spike timing dependent plasticity. Using memristors as synapses in neuromorphic circuits can potentially offer both high connectivity and high density required for efficient computing.
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            Short-term plasticity and long-term potentiation mimicked in single inorganic synapses.

            Memory is believed to occur in the human brain as a result of two types of synaptic plasticity: short-term plasticity (STP) and long-term potentiation (LTP; refs 1-4). In neuromorphic engineering, emulation of known neural behaviour has proven to be difficult to implement in software because of the highly complex interconnected nature of thought processes. Here we report the discovery of a Ag(2)S inorganic synapse, which emulates the synaptic functions of both STP and LTP characteristics through the use of input pulse repetition time. The structure known as an atomic switch, operating at critical voltages, stores information as STP with a spontaneous decay of conductance level in response to intermittent input stimuli, whereas frequent stimulation results in a transition to LTP. The Ag(2)S inorganic synapse has interesting characteristics with analogies to an individual biological synapse, and achieves dynamic memorization in a single device without the need of external preprogramming. A psychological model related to the process of memorizing and forgetting is also demonstrated using the inorganic synapses. Our Ag(2)S element indicates a breakthrough in mimicking synaptic behaviour essential for the further creation of artificial neural systems that emulate characteristics of human memory.
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              A functional hybrid memristor crossbar-array/CMOS system for data storage and neuromorphic applications.

              Crossbar arrays based on two-terminal resistive switches have been proposed as a leading candidate for future memory and logic applications. Here we demonstrate a high-density, fully operational hybrid crossbar/CMOS system composed of a transistor- and diode-less memristor crossbar array vertically integrated on top of a CMOS chip by taking advantage of the intrinsic nonlinear characteristics of the memristor element. The hybrid crossbar/CMOS system can reliably store complex binary and multilevel 1600 pixel bitmap images using a new programming scheme. © 2011 American Chemical Society
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                Author and article information

                Journal
                Nature
                Nature
                Springer Nature
                0028-0836
                1476-4687
                May 2015
                May 7 2015
                May 2015
                : 521
                : 7550
                : 61-64
                Article
                10.1038/nature14441
                25951284
                5335cf61-0e60-4ae9-9a5c-354bad46ba88
                © 2015

                http://www.springer.com/tdm

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