Event-based Signal Processing for Radioisotope Identification

TL;DR

This paper introduces an event-based signal processing approach and neuromorphic processor design to reduce power consumption in radioisotope identification compared to traditional frame-based methods.

Contribution

It proposes a novel event-based processing method and a neuromorphic processor design for more efficient radioisotope identification.

Findings

Reduced power overhead demonstrated

Efficient event-based processing framework established

Neuromorphic processor design outlined

Abstract

This paper identifies the problem of unnecessary high power overhead of the conventional frame-based radioisotope identification process and proposes an event-based signal processing process to address the problem established. It also presents the design flow of the neuromorphic processor.