A comparison of Extended Kalman Filter and Levenberg-Marquardt methods for neural network training

Abstract

This paper presents a performance comparison of both the Levenverg-Marquardt and Extended Kalman Filter methods for neural network training. As a testbed, an indoor localization problem was solved by the neural network from the RSSI data obtained through a experimental measurement. Both methods were used to train the network, and the MSE (mean squared error) was employed as the performance metric.