Engineering Commons^™

A Hardware-Deployable Neuromorphic Solution For Encoding And Classification Of Electronic Nose Data, Anup Vanarse, Alexander Rassau, Peter Van Der Made

Research outputs 2014 to 2021

In several application domains, electronic nose systems employing conventional data processing approaches incur substantial power and computational costs and limitations, such as significant latency and poor accuracy for classification. Recent developments in spike-based bio-inspired approaches have delivered solutions for the highly accurate classification of multivariate sensor data with minimized computational and power requirements. Although these methods have addressed issues related to efficient data processing and classification accuracy, other areas, such as reducing the processing latency to support real-time application and deploying spike-based solutions on supported hardware, have yet to be studied in detail. Through this investigation, we proposed a spiking …