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In this paper we develop the concept of implementing pattern recognition algorithms in analog memristor networks. First, a device model is presented with experimental results demonstrating the feasibility of using WOx-based memristors to represent the tunable weights in a neural network. Next, simulation results demonstrate that an array of these memristors can be used to implement an unsupervised...
We show resistive switching effects in memristive devices exhibit significant stochasticity. When the switching is dominated by a single filament, the switching time is fully random and shows a broad distribution. However, the switching distribution can be predicted and responds well to controlled changes in the programming conditions. The native stochastic characteristic can be used to generate random...
We show a Field-Programmable Analog Array complemented with post-processed memristors (FPAA/memristor hybrid circuit), and present it as a platform for analog signal processing. The FPAA is fabricated on CMOS and uses floating-gate transistors (FGT) to realize programmable wiring fabrics and analog computing resources. The memristors, post-processed on top of the FPAA, are analog, which means that...
We report the fabrication, modeling and implementation of nanoscale tungsten-oxide (WOx) memristive (memristor) devices for neuromorphic applications. The device behaviors can be predicted accurately by considering both ion drift and diffusion. Short-term memory and memory enhancement phenomena, and the effects of spike rate, timing and associativity have been demonstrated. SPICE modeling has been...
This paper describes how memristors, together with CMOS transistors (CMOS-memristor hybrids), could be used for analog arithmetic within cellular (locally connected, regular) computing arrays, i.e., cellular nanoscale networks (CNN). Elementary analog programming of memristors and copying memristance values are described. Also, we show how memristors could be used for addition, subtraction, multiplication...
We describe a generic exponential model with four parameters for thin-film memristive devices. This model is used to analyze the time dependency of the threshold voltage which defines the transition between non-programming and programming phases of the device. A relationship between timescale of operation and threshold voltage is derived. Furthermore, self-terminating programming is considered using...
We review the recent progress on the development of two-terminal resistive devices (memristors). Devices based on solid-state electrolytes (e.g. a-Si) have been shown to possess a number of promising performance metrics such as yield, on/off ratio, switching speed, endurance and retention suitable for memory or reconfigurable circuit applications. In addition, devices with incremental resistance changes...
We report studies on nanoscale Si-based memristive devices for memory and neuromorphic applications. The devices are based on ion motion inside an insulating a-Si matrix. Digital devices show excellent performance metrics including scalability, speed, ON/OFF ratio, endurance and retention. High density non-volatile memory arrays based on a crossbar structure have been fabricated and tested. Devices...
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