Related papers: Switch Elements with S-Shaped Current-Voltage Char…

Spiking neural networks (SNNs) that enable low-power design on edge devices have recently attracted significant research. However, the temporal characteristic of SNNs causes high latency, high bandwidth and high energy consumption for the…

Developing electronic devices capable of emulating biological functions is essential for advancing brain-inspired computation paradigms such as neuromorphic computing. In recent years, two-dimensional materials have emerged as promising…

The three-dimensional (3D) Fitzhugh-Nagumo neuron model with inertia was shown to exhibit a chaotic mixed-mode dynamics composed of large-amplitude spikes separated by an irregular number of small-amplitude chaotic oscillations. In contrast…

Computation on a large volume of data at high speed and low power requires energy-efficient computing architectures. Spiking neural network (SNN) with bio-inspired spike-timing-dependent plasticity learning (STDP) is a promising solution…

Hardware spiking neural networks hold the promise of realizing artificial intelligence with high energy efficiency. In this context, solid-state and scalable memristors can be used to mimic biological neuron characteristics. However, these…

Prevailing models of resistive switching arising from electrochemical formation of conducting filaments across solid state ionic conductors commonly attribute the observed polarity of the voltage-biased switching to the sequence of the…

The paper highlights the role of a positive feedback gating mechanism at the cellular level in the robust- ness and modulation properties of rhythmic activities at the circuit level. The results are presented in the context of half-center…

We propose a new orbital controlled model to explain the gate field induced switching of current in a semiconducting PbS-nanowire junction. A single particle scattering formalism in conjunction with a posteriori density functional approach…

We study $I$-$V$ characteristics of periodic square Nb wire networks as a function of temperature in a transverse magnetic field, with a focus on three fillings 2/5, 1/2, and 0.618 that represent very different levels of incommensurability.…

We consider an open quantum system in contact with fermionic metallic reservoirs in a nonequilibrium setup. For the case of spin, orbital or potential fluctuations, we present a systematic formulation of real-time renormalization group at…

We have measured the critical phase change conditions induced by electrical pulses in Ge2Sb2Te5 nanopillar phase change memory devices by constructing a comprehensive resistance map as a function of pulse parameters (width, amplitude and…

Spintronic neurons which emit sharp voltage spikes are required for the realization of hardware neural networks enabling fast data processing with low-power consumption. In many neuroscience and computer science models, neurons are…

Neuromorphic computing refers to brain-inspired computers, that differentiate it from von Neumann architecture. Analog VLSI based neuromorphic circuits is a current research interest. Two simpler spiking integrate and fire neuron model…

Spin-torque nano-oscillators can emulate neurons at the nanoscale. Recent works show that the non-linearity of their oscillation amplitude can be leveraged to achieve waveform classification for an input signal encoded in the amplitude of…

We explore how non-equilibrium noise affects spin-torque switching elements and oscillators. To do so we first discuss the deterministic dynamics of magnetic tunnel junctions, introducing a convenient set of slow and fast degrees of…

An attempt to determine theoretically the highly non-linear current-voltage (I-V) characteristics of polycrystalline semiconductors, such as ZnO-based varistors, is made from the electrical properties of individual grain boundaries under dc…

A spin-thermo-electronic valve with the free layer of exchange-spring type and inverse magnetoresistance is investigated. The structure has S-shaped current-voltage characteristics and can exhibit spontaneous oscillations when integrated…

We examine the response of type II excitable neurons to trains of synaptic pulses, as a function of the pulse frequency and amplitude. We show that the resonant behavior characteristic of type II excitability, already described for harmonic…

Artificial neural networks can harness stochasticity in multiple ways to enable a vast class of computationally powerful models. Electronic implementation of such stochastic networks is currently limited to addition of algorithmic noise to…

Due to the limitations of realizing artificial neural networks on prevalent von Neumann architectures, recent studies have presented neuromorphic systems based on spiking neural networks (SNNs) to reduce power and computational cost.…