Dynamical systems for sensor fusion and classification

Abstract

In this paper we show how the dynamic approach to sensor fusion, presented on IGARSS 1999 and IGARSS 2000 can be applied to the problem of classifying noisy sensor data. The idea is to use the output of the dynamic sensor fusion algorithm as input for a system of winner-takes-all dynamics in which different classes compete with each other. In this way, transitions between classes are brought about by bifurcations between stable states of a dynamical system. For the example of classifying sea ice types from SAR image data, we will show that, due to the defined time scale of these bifurcations, the dynamic approach is advantageous for classifying properties of real physical systems.