Related papers: Resistive communications based on neuristors
This paper investigates the potentials of using a hybrid memristor CMOS technology, called MeMOS, for the realisation of ternary adders. Ternary adders exploit the qualitative advantage of multi-value storage capability of memristors…
We experimentally demonstrate a proof-of-principle implementation of an almost ideal memristor - a two-terminal circuit element whose resistance is approximately proportional to the integral of the input signal over time. The demonstrated…
The memristors are expected to be fundamental devices for neuromorphic systems and switching applications. For example, the device made of a sandwiched layer of poly(N-vinylcarbazole) and reduced graphene composite between asymmetric…
Amorphous insulators have localized wave functions that decay with the distance $r$ following exp($-r/\zeta$). Since nanoscale conduction is not excluded at $r<\zeta$, one may use amorphous insulators and take advantage of their size effect…
We present the design of a new passive wireless communication system that does not rely on ambient or generated RF sources. Instead, we exploit the Johnson (thermal) noise generated by a resistor to transmit information bits wirelessly. By…
Recent results in adaptive matter revived the interest in the implementation of novel devices able to perform brain-like operations. Here we introduce a training algorithm for a memristor network which is inspired in previous work on…
Memristors, uniquely characterized by their pinched hysteresis loop fingerprints, have attracted significant research interest over the past decade, due to their enormous potential for novel computation and artificial intelligence…
Single-molecule magnets weakly coupled to two ferromagnetic leads act as memory devices in electronic circuits---their response depends on history, not just on the instantaneous applied voltage. We show that magnetic anisotropy introduces a…
We show theoretically that networks of membrane memcapacitive systems -- capacitors with memory made out of membrane materials -- can be used to perform a complete set of logic gates in a massively parallel way by simply changing the…
Memristors have emerged as key candidates for beyond-von-Neumann neuromorphic or in-memory computing owing to the feasibility of their ultrahigh-density three-dimensional integration and their ultralow energy consumption. A memristor is…
We analyzed micrometer-scale titanium-niobium-oxide prototype memristors, which exhibited low write-power (<3 {\mu}W) and energy (<200 fJ/bit/{\mu}m2), low read-power (~nW), and high endurance (>millions of cycles). To understand their…
Recent advancements in reservoir computing research have created a demand for analog devices with dynamics that can facilitate the physical implementation of reservoirs, promising faster information processing while consuming less energy…
Memristive systems, namely resistive systems with memory, are attracting considerable attention due to their ubiquity in several phenomena and technological applications. Here, we show that even the simplest one-dimensional network formed…
In almost all of the currently working circuits, especially in analog circuits implementing signal processing applications, basic arithmetic operations such as multiplication, addition, subtraction and division are performed on values which…
Implication logic gates that are based on volatile memristors are demonstrated experimentally with the use of relay-based volatile memristor emulators of an original design. The fabricated logic circuit involves two volatile memristors and…
Two-dimensional (2D) materials are popular candidates for emerging nanoscale devices, including memristors. Resistive switching (RS) in such 2D material memristors has been attributed to the formation and dissolution of conductive filaments…
Advanced neural interfaces mediate a bio-electronic link between the nervous system and microelectronic devices, bearing great potential as innovative therapy for various diseases. Spikes from a large number of neurons are recorded leading…
Reservoir Computing is a type of recursive neural network commonly used for recognizing and predicting spatio-temporal events relying on a complex hierarchy of nested feedback loops to generate a memory functionality. The Reservoir…
Memristors have shown promising features for enhancing neuromorphic computing concepts and AI hardware accelerators. In this paper, we present a user-friendly software infrastructure that allows emulating a wide range of neuromorphic…
Neuromorphic computing --- brainlike computing in hardware --- typically requires myriad CMOS spiking neurons interconnected by a dense mesh of nanoscale plastic synapses. Memristors are frequently citepd as strong synapse candidates due to…