Message Passing-based System Identification for NARMAX Models

Abstract

We present a variational Bayesian identification procedure for polynomial NARMAX models based on message passing on a factor graph. Message passing allows us to obtain full posterior distributions for regression coefficients, precision parameters and noise instances by means of local computations distributed according to the factorization of the dynamic model. The posterior distributions are important to shaping the predictive distribution for outputs, and ultimately lead to superior model performance during 1-step ahead prediction and simulation.

Albert Podusenko

Chief Executive Officer LazyDynamics

Albert Podusenko is a founder & CEO of Lazy Dynamics.

Semih Akbayrak

Former PhD student

Former researcher at BIASlab.

İsmail Şenöz

Chief Scientist
LazyDynamics

Ismail Senoz is a co-founder & chief scientist of Lazy Dynamics

Wouter Kouw

Assistant professor

I am an assistant professor working on active inference for mobile robots.