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Hardware implementation of memristor-based artificial neural networks
Artificial Intelligence (AI) is currently experiencing a bloom driven by deep learning (DL)
techniques, which rely on networks of connected simple computing units operating in …
techniques, which rely on networks of connected simple computing units operating in …
Solution-processed memristors: performance and reliability
Memristive devices are gaining importance in the semiconductor industry for applications in
information storage, artificial intelligence cryptography and telecommunication. Memristive …
information storage, artificial intelligence cryptography and telecommunication. Memristive …
Hybrid 2D–CMOS microchips for memristive applications
Exploiting the excellent electronic properties of two-dimensional (2D) materials to fabricate
advanced electronic circuits is a major goal for the semiconductor industry,. However, most …
advanced electronic circuits is a major goal for the semiconductor industry,. However, most …
Integrated memory devices based on 2D materials
With the advent of the Internet of Things and big data, massive data must be rapidly
processed and stored within a short timeframe. This imposes stringent requirements on …
processed and stored within a short timeframe. This imposes stringent requirements on …
Wafer‐Scale Memristor Array Based on Aligned Grain Boundaries of 2D Molybdenum Ditelluride for Application to Artificial Synapses
Abstract 2D materials have attracted attention in the field of neuromorphic computing
applications, demonstrating the potential for their use in low‐power synaptic devices at the …
applications, demonstrating the potential for their use in low‐power synaptic devices at the …
SPICE implementation of the dynamic memdiode model for bipolar resistive switching devices
This paper reports the fundamentals and the SPICE implementation of the Dynamic
Memdiode Model (DMM) for the conduction characteristics of bipolar-type resistive switching …
Memdiode Model (DMM) for the conduction characteristics of bipolar-type resistive switching …
Nonmasking-based reservoir computing with a single dynamic memristor for image recognition
Reservoir computing has been widely used in temporal information processing, and the
presentation of time-delayed reservoir computing systems effectively reduces the difficulty of …
presentation of time-delayed reservoir computing systems effectively reduces the difficulty of …
Nano‐Memristors with 4 mV Switching Voltage Based on Surface‐Modified Copper Nanoparticles
The development of memristors operating at low switching voltages< 50 mV can be very
useful to avoid signal amplification in many types of circuits, such as those used in …
useful to avoid signal amplification in many types of circuits, such as those used in …
Synaptic plasticity features and neuromorphic system simulation in AlN-based memristor devices
In this paper, we show various memory characteristics of the Ag/AlN/TiN devices for
neuromorphic systems. We verified the thickness and the components of the device stack by …
neuromorphic systems. We verified the thickness and the components of the device stack by …
Xbar-partitioning: a practical way for parasitics and noise tolerance in analog imc circuits
Conventional in-memory computing (IMC) architectures consist of analog memristive
crossbars to accelerate matrix-vector multiplication (MVM), and digital functional units to …
crossbars to accelerate matrix-vector multiplication (MVM), and digital functional units to …