Related papers: Practical Demonstration of a Memristive Fuse
The recent co-optimization of memristive technologies and programming algorithms enabled neural networks training with in-memory computing systems. In this context, novel analog filamentary conductive-metal-oxide (CMO)/HfOx redox-based…
Enhancing the switching speed of oxide-based memristive devices at a low voltage level is crucial for their use as non-volatile memory and their integration into emerging computing paradigms such as neuromorphic computing. Efforts to…
Memristors can mimic the functions of biological synapse, where it can simultaneously store the synaptic weight and modulate the transmitted signal. Here, we report Nb/Nb2O5/Pt based memristors with bipolar resistive switching, exhibiting…
Memristors are continuously tunable resistors that emulate synapses. Conceptualized in the 1970s, they traditionally operate by voltage-induced displacements of matter, but the mechanism remains controversial. Purely electronic memristors…
The translation of emerging application concepts that exploit Resistive Random Access Memory (ReRAM) into large-scale practical systems requires realistic, yet computationally efficient, empirical models that can capture all observed…
The advent of advanced neuronal interfaces offers great promise for linking brain functions to electronics. A major bottleneck in achieving this is real-time processing of big data that imposes excessive requirements on bandwidth, energy…
A number of memristive devices, mainly ReRAMs, have been reported to exhibit a unique non-zero crossing hysteresis attributed to the interplay of resistive and not yet fully understood `capacitive', and `inductive' effects. This work…
The potential of memristive devices is often seeing in implementing neuromorphic architectures for achieving brain-like computation. However, the designing procedures do not allow for extended manipulation of the material, unlike CMOS…
Memristors as emergent nano-electronic devices have been successfully fabricated and used in non-conventional and neuromorphic computing systems in the last years. Several behavioral or physical based models have been developed to explain…
We suggest electronic circuits with memristors (resistors with memory) that operate as memcapacitors (capacitors with memory) and meminductors (inductors with memory). Using a memristor emulator, the suggested circuits have been built and…
A memristive device is a novel passive device, which is essentially a resistor with memory. This device can be utilized for novel technical applications like neuromorphic computation. In this paper, we focus on anticipation - a capability…
Highly accurate and predictive models of resistive switching devices are needed to enable future memory and logic design. Widely used is the memristive modeling approach considering resistive switches as dynamical systems. Here we introduce…
A large number of simulation models have been proposed over the years to mimic the electrical behaviour of memristive devices. The models are based either on sophisticated mathematical formulations that do not account for physical and…
Nonlinearity is a crucial characteristic for implementing hardware security primitives or neuromorphic computing systems. The main feature of all memristive devices is this nonlinear behavior observed in their current-voltage…
Achieving reliable resistive switching in oxide-based memristive devices requires precise control over conductive filament (CF) formation and behavior, yet the fundamental relationship between oxide material properties and switching…
Memristor, one of the fundamental circuit elements, has promising applications in non-volatile memory and storage technology as it can theoretically achieve infinite states. Information can be stored independently in these states and…
Memristive devices, whose resistance can be controlled by applying a voltage and further retained, are attractive as possible circuit elements for neuromorphic computing. This new type of devices poses a number of both technological and…
Gradual switching between multiple resistance levels is desirable for analog in-memory computing using resistive random-access memory (RRAM). However, the filamentary switching of $HfO_x$-based conventional RRAM often yields only two stable…
This study investigates strategies for minimizing Joule losses in resistive random access memory (ReRAM) cells, which are also referred to as memristive devices. Typically, the structure of ReRAM cells involves a nanoscale layer of…
Nanoscale metal oxide memristors have potential in the development of brain-inspired computing systems that are scalable and efficient1-3. In such systems, memristors represent the native electronic analogues of the biological synapses.…