Related papers: Memristive Transfer Matrices
The transfer matrix is a powerful technique that can be applied to statistical mechanics systems as, for example, in the calculus of the entropy of the ice model. One interesting way to study such systems is to map it onto a 3-color…
Memristors have been at the forefront of nanoelectronics research for the last decade, offering a valuable component to reconfigurable computing. Their attributes have been studied extensively along with applications that leverage their…
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…
Resistive memories (RRAM) are promising candidates for replacing present nonvolatile memories and realizing storage class memories; hence resistance switching devices are of particular interest. These devices are typically memristive, with…
Analog computing based on memristor technology is a promising solution to accelerating the inference phase of deep neural networks (DNNs). A fundamental problem is to map an arbitrary matrix to a memristor crossbar array (MCA) while…
Memristors are promising next-generation memory candidates that are nonvolatile, possess low power requirements and are capable of nanoscale fabrication. In this article we physically realise and describe the use of organic memristors in…
Construction and training principles have been proposed and tested for an artificial neural network based on metal-oxide thin-film nanostructures possessing bipolar resistive switching (memristive) effect. Experimental electronic circuit of…
A memristor, a two-terminal nanodevice, has garnered substantial attention in recent years due to its distinctive properties and versatile applications. These nanoscale components, characterized by their simplicity of manufacture,…
The memristor is a device whose resistance changes depending on the polarity and magnitude of a voltage applied to the device's terminals. We design a minimalistic model of a regular network of memristors using structurally-dynamic cellular…
With power consumption becoming a critical processor design issue, specialized architectures for low power processing are becoming popular. Several studies have shown that neural networks can be used for signal processing and pattern…
As deep neural networks require tremendous amount of computation and memory, analog computing with emerging memory devices is a promising alternative to digital computing for edge devices. However, because of the increasing simulation time…
This paper proposes four quadrant analog multiplier using CMOS-memristor circuit. Currently, there are plenty of analog multipliers using resistors and CMOS transistors. They can attain perfect multiplication but have several disadvantages…
Brain inspired circuits can provide an alternative solution to implement computing architectures taking advantage of fault tolerance and generalisation ability of logic gates. In this brief, we advance over the memristive threshold circuit…
The Bessel filters are optimized to collect competent transient response due to a linear phase in the passband. In other words, during the filtering process, there will be comparatively impoverished frequency response with lower amplitude…
Memristors are low-power memory-holding resistors thought to be useful for neuromophic computing, which can compute via spike-interactions mediated through the device's short-term memory. Using interacting spikes, it is possible to build an…
With the increase of the speed of computers, timing and power requirements are becoming crucial for memory devices. The main objective of the paper is to modify 180nm CMOS sense amplifier design by using memristive devices and improve the…
Lifelong on-device learning is a key challenge for machine intelligence, and this requires learning from few, often single, samples. Memory augmented neural network has been proposed to achieve the goal, but the memory module has to be…
Digital memristive processing-in-memory overcomes the memory wall through a fundamental storage device capable of stateful logic within crossbar arrays. Dynamically dividing the crossbar arrays by adding memristive partitions further…
A content-addressable-memory compares an input search word against all rows of stored words in an array in a highly parallel manner. While supplying a very powerful functionality for many applications in pattern matching and search, it…
Different real-world cognitive tasks evolve on different relevant timescales. Processing these tasks requires memory mechanisms able to match their specific time constants. In particular, the working memory utilizes mechanisms that span…