Design of a robust memristive spiking neuromorphic system with unsupervised learning in hardware
MM Adnan, S Sayyaparaju, SD Brown… - ACM Journal on …, 2021 - dl.acm.org
Spiking neural networks (SNN) offer a power efficient, biologically plausible learning
paradigm by encoding information into spikes. The discovery of the memristor has …
paradigm by encoding information into spikes. The discovery of the memristor has …
A Data-Driven Stochastic Memristor Model for Integrated Circuit Simulation
Memristors have emerged as promising candidates for multi-level data storage, in-memory
processing, and neural networks since their intrinsic programmability of resistance states …
processing, and neural networks since their intrinsic programmability of resistance states …
A Variation-Aware CMOS Platform for Multi-Level Memristor Characterisation
Memristors could be potentially used in both multi-bit data storage and analogue
computation, thanks to their programmable resistance. However, there are three common …
computation, thanks to their programmable resistance. However, there are three common …
Design of Robust Memristor-Based Neuromorphic Circuits and Systems with Online Learning
S Sayyaparaju - 2020 - trace.tennessee.edu
Computing systems that are capable of performing human-like cognitive tasks have been an
area of active research in the recent past. However, due to the bottleneck faced by the …
area of active research in the recent past. However, due to the bottleneck faced by the …