The synapse is a crucial element in biological neural networks, but a simple electronic
equivalent has been absent. This complicates the development of hardware that imitates …

Hybrid CMOS/nanoelectronic circuits, combining CMOS chips with simple nanoelectronic
crossbar add-ons, may extend the exponential Moore-Law progress of microelectronics …

In this paper we present a very exciting overlap between emergent nanotechnology and
neuroscience, which has been discovered by neuromorphic engineers. Specifically, we are …

Metal-oxide memristors have emerged as promising candidates for hardware
implementation of artificial synapses–the key components of high-performance, analog …

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Memory effects are ubiquitous in nature and the class of memory circuit elements—which
includes memristive, memcapacitive, and meminductive systems—shows great potential to …

Adv. Mater. 2012, 24, 762–766 duration of a each pulse. For vmax, a value in excess of the
activation threshold vth≈ 0.35 V was required (see Supporting Information). The resulting …

Bio-inspired computing promises fundamentally different ways to advances in artificial
intelligence with extreme energy efficiency. Memristive technologies due to the non-volatility …

The memristor has been regarded as a promising candidate for constructing a neuromorphic
computing platform that is capable of confronting the bottleneck of the traditional von …

Memristor nanodevices have good properties for use as synapses to add dynamic learning
to neuromorphic networks implemented in crossbar-based CMOS/Nano hybrids. In this …