Independent Component Analysis Using RRAMs

M. E. Fouda, E. Neftci, A. Eltawil, F. Kurdahi
November 2018
PDF DOI
Type
Journal article
Publication
IEEE Transactions on Nanotechnology
blind source separation;feature extraction;Hebbian learning;independent component analysis;Laplace equations;neural nets;random-access storage;titanium compounds;unsupervised learning;Laplacian signals demixing;device variability;local unsupervised learning algorithm;resistive random-access memories;feature extraction;RRAM;asymmetric nonlinear weight update behavior;error-gated Hebbian rule;ICA;independent component analysis;blind source separation problem;neuromorphic circuits;TiO2;Programming;Switches;Heuristic algorithms;Independent component analysis;Feature extraction;Training;Hardware;RRAMs;memristor;ICA;unsupervised learning;brain-inspired learning