Related papers: Nonlinear behavior of memristive devices for hardw…
Locally-active memristors are a class of emerging nonlinear dynamic circuit elements that hold promise for scalable yet biomimetic neuromorphic circuits. Starting from a physics-based compact model, we performed small-signal linearization…
Reservoir computing is a highly efficient machine learning framework for processing temporal data by extracting features from the input signal and mapping them into higher dimensional spaces. Physical reservoir layers have been realized…
Quantum computer technology harnesses the features of quantum physics for revolutionizing information processing and computing. As such, quantum computers use physical quantum gates that process information unitarily, even though the final…
Emerging non-volatile memories (NVMs) represent a disruptive technology that allows a paradigm shift from the conventional von Neumann architecture towards more efficient computing-in-memory (CIM) architectures. Several instrumentation…
Stochastic behaviors of resistive random access memory (RRAM) play an important role in the design of cross-point memory arrays. A Monte Carlo compact model of oxide RRAM is developed and calibrated with experiments on various device stack…
The functionality of logic and memory elements in current electronics is based on multi-stability, driven either by manipulating local concentrations of electrons in transistors, or by switching between equivalent states of a material with…
In this paper, the nonlinear mode conversion of extraordinary waves in nonuniform magnetized plasmas is studied using the variational symplectic particle-in-cell simulation. The accuracy of the nonlinear simulation is guaranteed by the…
The tendency for flows in microfluidic systems to behave linearly poses a challenge for designing integrated flow control schemes to carry out complex fluid processing tasks. This hindrance has led to the use of numerous external control…
Intracellular recordings of cortical neurons in vivo display intense subthreshold membrane potential (Vm) activity. The power spectral density (PSD) of the Vm displays a power-law structure at high frequencies (>50 Hz) with a slope of about…
The morphology and dimension of the conductive filament formed in a memristive device are strongly influenced by the thickness of its switching medium layer. Aggressive scaling of this active layer thickness is critical towards reducing the…
The inertia of trapping and detrapping of nonequilibrium charge carriers affects the electrochemical and transport properties of both bulk and nanoscopic structures in a very peculiar way. An emerging memory response with a hysteresis in…
Multistability -- the emergence of multiple stable states under identical conditions -- is a hallmark of nonlinear complexity and an enabling mechanism for multilevel optical memory and photonic computing. Its realization in a compact…
The dynamics of memristive device in response to neuron-like signals and coupling electronic neurons via memristive device has been investigated theoretically and experimentally. The simplest experimental system consists of electronic…
Memristive systems were proposed in 1976 by Leon Chua and Sung Mo Kang as a model for 2-terminal passive nonlinear dynamical systems which exhibit memory effects. Such systems were originally shown to be relevant to the modeling of action…
Macroscopic phase coherence in superconductors enables quantum interference and phase manipulation at realistic device length scales. Numerous superconducting electronic devices are based on the modulation of the supercurrent in…
Brain dynamics can exhibit narrow-band nonlinear oscillations and multistability. For a subset of disorders of consciousness and motor control, we hypothesize that some symptoms originate from the inability to spontaneously transition from…
In this report, we lay the foundation for amplitude noise and phase noise analysis in nonlinear devices. We build a theoretical framework that helps us to analyze extremely difficult problems which include both nonlinearity and noise of…
Memristive devices hold promise to improve the scale and efficiency of machine learning and neuromorphic hardware, thanks to their compact size, low power consumption, and the ability to perform matrix multiplications in constant time.…
We discuss the physical properties of realistic memristive, memcapacitive and meminductive systems. In particular, by employing the well-known theory of response functions and microscopic derivations, we show that resistors, capacitors and…
We investigate the origin of the experimentally observed varying current-frequency nonlinearity of the propagating spin wave mode in nano-contact spin torque oscillators. Nominally identical devices with 100 nm diameter are characterized by…