Results 61 to 70 of about 25,251 (300)
Electronic and Photoelectronic Memristors Based on 2D Materials
Advanced Electronic Materials, 2022 Next‐generation memristive devices and neuromorphic computing have many fantastic properties in breaking down the memory walls of conventional von Neumann structures.
Kai Tang +6 more
doaj +1 more source
Analytical Computation of the Area of Pinched Hysteresis Loops of Ideal Mem-Elements [PDF]
, 2013 The memory elements, memristor being the best known of them, driven by a periodical waveform exhibit the well-known pinched hysteresis loops. The hysteresis is caused by a memory effect which results in a nonzero area closed within the loop.
Biolek, Dalibor +2 more
core +1 more source
, 2017 We have calculated the key characteristics of associative (content-addressable) spatial-temporal memories based on neuromorphic networks with restricted connectivity - "CrossNets".
Gavrilov, Dmitri +2 more
core +2 more sources
Applied Physics Letters, 2017 Based on the differential conformal transformation in the fractional order, we defined the fractional memristor in contrast to the traditional (integer-order) memristor. As an example, a typical spin-transfer torque (STT) memristor (with the asymmetric resistance hysteresis) was proved to be a 0.8 fractional memristor.
Frank Z. Wang +4 more
openaire +2 more sources
Surface Diffusion in SnTe‐PbTe Monolayer Lateral Heterostructures
Advanced Functional Materials, EarlyView.The lateral heterostructures between 2D materials often suffer from the interdiffusion at the interfaces. Here, a surface diffusion mechanism is found to be dominating at the interfaces between semiconducting SnTe and PbTe monolayers. Atomically sharp interfaces can be achieved by suppressing this diffusion process. ABSTRACT The construction of complex
Jing‐Rong Ji +9 more
wiley +1 more source
Halide perovskite memristors as flexible and reconfigurable physical unclonable functions
Nature Communications, 2021 Despite the impressive demonstrations with silicon and oxide memristors, realizing efficient roots of trust for resource-constrained hardware remains a challenge.
Rohit Abraham John +8 more
doaj +1 more source
Versatile stochastic dot product circuits based on nonvolatile memories for high performance neurocomputing and neurooptimization. [PDF]
, 2019 The key operation in stochastic neural networks, which have become the state-of-the-art approach for solving problems in machine learning, information theory, and statistics, is a stochastic dot-product.
Mahmoodi, MR, Prezioso, M, Strukov, DB
core +1 more source
Designing Asymmetric Memristive Behavior in Proton Mixed Conductors for Neuromorphic Applications
Advanced Functional Materials, EarlyView.Protonic devices that couple ionic and electronic transport are demonstrated as bioinspired neuromorphic elements. The devices exhibit rubber‐like asymmetric memristive behavior with slow voltage‐driven conductance increase and rapid relaxation, enabling simplified read–write operation.
Nada H. A. Besisa +6 more
wiley +1 more source
Silk Protein Based Volatile Threshold Switching Memristors for Neuromorphic Computing
Advanced Electronic Materials, 2022 Memristors based neuromorphic devices can efficiently process complex information and fundamentally overcome the bottleneck of traditional computing based on von Neumann architecture.
Momo Zhao +13 more
doaj +1 more source
Reliable SPICE Simulations of Memristors, Memcapacitors and Meminductors [PDF]
, 2013 Memory circuit elements, namely memristive, memcapacitive and meminductive systems, are gaining considerable attention due to their ubiquity and use in diverse areas of science and technology. Their modeling within the most widely used environment, SPICE,
Biolek, Dalibor +2 more
core +2 more sources