Related papers: Is Spiking Logic the Route to Memristor-Based Comp…
The random walk is a fundamental stochastic process that underlies many numerical tasks in scientific computing applications. We consider here two neural algorithms that can be used to efficiently implement random walks on spiking…
Memristive neuromorphic systems are designed to emulate human perception and cognition, where the memristor states represent essential historical information to perform both low-level and high-level tasks. However, current systems face…
Spiking neural network is a kind of neuromorphic computing that is believed to improve the level of intelligence and provide advantages for quantum computing. In this work, we address this issue by designing an optical spiking neural…
Memristive Processing In-Memory (PIM) is one of the promising techniques for overcoming the Von-Neumann bottleneck. Reduction of data transfer between processor and memory and data processing by memristors in data-intensive applications…
Digital processing-in-memory (PIM) architectures are rapidly emerging to overcome the memory-wall bottleneck by integrating logic within memory elements. Such architectures provide vast computational power within the memory itself in the…
The increasing need for intelligent sensors in a wide range of everyday objects requires the existence of low power information processing systems which can operate autonomously in their environment. In particular, merging and processing…
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…
Nanoscale resistive switching devices (memristive devices or memristors) have been studied for a number of applications ranging from non-volatile memory, logic to neuromorphic systems. However a major challenge is to address the potentially…
Memristors have demonstrated immense potential as building blocks in future adaptive neuromorphic architectures. Recently, there has been focus on emulating specific synaptic functions of the mammalian nervous system by either tailoring the…
In the rapid evolution of next-generation brain-inspired artificial intelligence and increasingly sophisticated electromagnetic environment, the most bionic characteristics and anti-interference performance of spiking neural networks show…
Network of neurons in the brain apply - unlike processors in our current generation of computer hardware - an event-based processing strategy, where short pulses (spikes) are emitted sparsely by neurons to signal the occurrence of an event…
The increasing rise in machine learning and deep learning applications is requiring ever more computational resources to successfully meet the growing demands of an always-connected, automated world. Neuromorphic technologies based on…
Processing-in-memory (PIM) is attractive to overcome the limitations of modern computing systems. Numerous PIM systems exist, varying by the technologies and logic techniques used. Successful operation of specific logic functions is crucial…
Brain-inspired computing aims to mimic cognitive functions like associative memory, the ability to recall complete patterns from partial cues. Memristor technology offers promising hardware for such neuromorphic systems due to its potential…
In-memory computing (IMC) with single instruction multiple data (SIMD) setup enables memory to perform operations on the stored data in parallel to achieve high throughput and energy saving. To instruct a SIMD IMC hardware to compute a…
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…
There is unprecedented development in machine learning, exemplified by recent large language models and world simulators, which are artificial neural networks running on digital computers. However, they still cannot parallel human brains in…
Memtranstor that correlates charge and magnetic flux via nonlinear magnetoelectric effects has a great potential in developing next-generation nonvolatile devices. In addition to multi-level nonvolatile memory, we demonstrate here that…
Exploiting spin degree of freedom of electron a new proposal is given to characterize spin-based logical operations using a quantum interferometer that can be utilized as a programmable spin logic device (PSLD). The ON and OFF states of…
Current advances in emerging memory technologies enable novel and unconventional computing architectures for high-performance and low-power electronic systems, capable of carrying out massively parallel operations at the edge. One emerging…