Parameter Estimation of Hidden Diffusion Processes: Particle Filter vs. Modified Baum-Welch Algorithm

TL;DR

This paper introduces a modified Baum-Welch algorithm for estimating parameters of hidden diffusion processes, demonstrating superior accuracy over particle filters in noisy periodic systems.

Contribution

It presents an improved Baum-Welch algorithm based on transition matrix parametrization and compares its performance to particle filters.

Findings

Modified Baum-Welch outperforms particle filters in accuracy

Algorithm effectively estimates parameters in noisy systems

Comparison demonstrates advantages in specific applications

Abstract

We propose a new method for the estimation of parameters of hidden diffusion processes. Based on parametrization of the transition matrix, the Baum-Welch algorithm is improved. The algorithm is compared to the particle filter in application to the noisy periodic systems. It is shown that the modified Baum-Welch algorithm is capable of estimating the system parameters with better accuracy than particle filters.