A digital memristor emulator for FPGA-based artificial neural networks
Document typeConference report
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Rights accessRestricted access - publisher's policy
FPGAs are reconfigurable electronic platforms, well-suited to implement complex artificial neural networks (ANNs). To this end, the compact hardware (HW) implementation of artificial synapses is an important step to obtain human brain-like functionalities at circuit-level. In this context, the memristor has been proposed as the electronic analogue of biological synapses, but the price of commercially available samples still remains high, hence motivating the development of HW emulators. In this work we present the first digital memristor emulator based upon a voltagecontrolled threshold-type bipolar memristor model. We validate its functionality in low-cost yet powerful FPGA families. We test its suitability for complex memristive circuits and prove its synaptic properties in a small associative memory via a perceptron ANN.
CitationVourkas, I., Abusleme, A., Ntinas, V., Sirakoulis, G., Rubio, A. A digital memristor emulator for FPGA-based artificial neural networks. A: IEEE International Verification and Security Workshop. "2016 1st IEEE International Verification and Security Workshop (IVSW 2016): Sant Feliu de Guixols, Spain: 4-6 July 2016". Sant Feliu de Guixols, Girona: Institute of Electrical and Electronics Engineers (IEEE), 2016, p. 54-57.