相关论文: Memcapacitors and Meminductors are Overunity Syste…

Universal properties of efficiency at maximum power are investigated in a general setting. In particular, it is demonstrated how successive symmetries placed upon the dynamics manifest themselves at the macroscopic level. A general…

Simulation frameworks such MemTorch, DNN+NeuroSim, and aihwkit are commonly used to facilitate the end-to-end co-design of memristive machine learning (ML) accelerators. These simulators can take device nonidealities into account and are…

In this work, we analyzed an anomalous effect verified from symmetrical capacitor devices, working in very high electric potentials. The mastery of that effect could mean in the future the possible substitution of propulsion technology…

The present study proposes the use of intelligent metasurfaces in the design of products, as enforcers of circular economy principles. Intelligent metasurfaces can tune their physical properties (electromagnetic, acoustic, mechanical) by…

Artificial intelligence is widely used in everyday life. However, an insufficient computing efficiency due to the so-called von Neumann bottleneck cannot satisfy the demand for real-time processing of rapidly growing data. Memristive…

Digital equipment such as computers, telecommunication systems and instruments use microprocessors that operate at high frequencies allowing them to carry out millions or even billions of operations per second. A disturbance in the…

The progress of the Internet of Things(IoT) technologies and applications requires the efficient low power circuits and architectures to maintain and improve the performance of the increasingly growing data processing systems. Memristive…

Topological Insulator-based devices can transport electrons/photons at the surfaces of materials without any back reflections, even in the presence of obstacles. Topological properties have recently been studied using non-reciprocal…

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.…

A representation of current is presented which can account for ideal conduction and distinguish superconductors, superfluids, ideal, and non-ideal conductors. The idea of the scheme is that different current operators and transport weights…

Recording reliably extracellular neural activities isan essential prerequisite for the development of bioelectronicsand neuroprosthetic applications. Recently, a fully differential,2-stage, integrating pre-amplifier was proposed for…

We introduce the notions of semi-uniform input-to-state stability and its subclass, polynomial input-to-state stability, for infinite-dimensional systems. We establish a characterization of semi-uniform input-to-state stability based on…

The embedded DRAM (eDRAM) is more and more used in System On Chip (SOC). The integration of the DRAM capacitor process into a logic process is challenging to get satisfactory yields. The specific process of DRAM capacitor and the low…

Memristor crossbars are circuits capable of performing analog matrix-vector multiplications, overcoming the fundamental energy efficiency limitations of digital logic. They have been shown to be effective in special-purpose accelerators for…

Nowadays superconductors serve in numerous applications, from high-field magnets to ultra-sensitive detectors of radiation. Mesoscopic superconducting devices, i.e. those with nanoscale dimensions, are in a special position as they are…

Transformers have reached remarkable success in sequence modeling. However, these models have efficiency issues as they need to store all the history token-level representations as memory. We present Memformer, an efficient neural network…

High-fidelity numerical methods that model the physical layout of a device are essential for the design of many technologies. For methods that characterize electromagnetic effects, these numerical methods are referred to as computational…

Magnetoelectric susceptibility of a metamaterial built from split ring resonators have been investigated both experimentally and within an equivalent circuit model. The absolute values have been shown to exceed by two orders of magnitude…

A model of superconductivity is proposed taking into account repulsive particle interaction, mesoscopic phase separation and softening of crystalline lattice. These features are typical of many high-temperature superconductors. The main…

Neuro-inspired computing architectures are one of the leading candidates to solve complex, large-scale associative learning problems. The two key building blocks for neuromorphic computing are the synapse and the neuron, which form the…