With the incorporation of tailorable organic electronic materials as channel and storage
materials, organic field‐effect transistor (OFET)‐based memory has become one of the most …

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 …

Memristors as electronic artificial synapses have attracted increasing attention in
neuromorphic computing. Emulation of both “learning” and “forgetting” processes requires a …

Memristors have attracted broad interest as a promising candidate for future memory and
computing applications. Particularly, it is believed that memristors can effectively implement …

Memristive nanodevices can feature a compact multilevel nonvolatile memory function, but
are prone to device variability. We propose a novel neural network-based computing …

Neuromorphic systems are gaining increasing importance in an era where CMOS digital
computing techniques are reaching physical limits. These silicon systems mimic extremely …

We propose an original design for a neuron-inspired photonic computational primitive for a
large-scale, ultrafast cognitive computing platform. The laser exhibits excitability and …

Novel information processing techniques are being actively explored to overcome
fundamental limitations associated with CMOS scaling. A new paradigm of adaptive …

Emulating key synaptic functions in electronic devices is quite significant in bioinspired
applications. Artificial synaptic thin film transistors (TFT) offer a promising solution for …

We propose a design methodology to exploit adaptive nanodevices (memristors), virtually
immune to their variability. Memristors are used as synapses in a spiking neural network …