Engineering Commons^™

Fast And Accurate Sparse Coding Of Visual Stimuli With A Simple, Ultra-Low-Energy Spiking Architecture, Walt Woods, Christof Teuscher

Electrical and Computer Engineering Faculty Publications and Presentations

Memristive crossbars have become a popular means for realizing unsupervised and supervised learning techniques. Often, to preserve mathematical rigor, the crossbar itself is separated from the neuron capacitors. In this work, we sought to simplify the design, removing extraneous components to consume significantly lower power at a minimal cost of accuracy. This work provides derivations for the design of such a network, named the Simple Spiking Locally Competitive Algorithm, or SSLCA, as well as CMOS designs and results on the CIFAR and MNIST datasets. Compared to a non-spiking model which scored 33% on CIFAR-10 with a single-layer classifier, this hardware …