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Message Passing-Based Inference for Time-Varying Autoregressive Models

Time-varying autoregressive (TVAR) models are widely used for modeling of non-stationary signals. Unfortunately, online joint adaptation of both states and parameters in these models remains a challenge. In this paper, we represent the TVAR model by a factor graph and solve the inference problem by...

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Principais autores: Albert Podusenko, Wouter M. Kouw, Bert de Vries
פורמט: Artigo
שפה:Inglês
יצא לאור: MDPI AG 2021-05-01
סדרה:Entropy
נושאים:
Bayesian inference
free energy
factor graph
hybrid message passing
model selection
non-stationary systems
גישה מקוונת:https://www.mdpi.com/1099-4300/23/6/683
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