A Time-Varying Autoregressive Model for Characterizing Nonstationary Processes
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Signal Processing Letters"
DOI: 10.1109/lsp.2018.2880086
Abstract: This letter presents a time-varying autoregressive (TVAR) model aiming to characterize nonstationary behaviors often observed in real-world processes, which cannot be properly described by autoregressive processes such as first-order Markov and random-walk models. Specifically, general… read more here.
Keywords: varying autoregressive; autoregressive model; tvar model; model ... See more keywords
Using linear parameter varying autoregressive models to measure cross frequency couplings in EEG signals
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Human Neuroscience"
DOI: 10.3389/fnhum.2022.915815
Abstract: For years now, phase-amplitude cross frequency coupling (CFC) has been observed across multiple brain regions under different physiological and pathological conditions. It has been suggested that CFC serves as a mechanism that facilitates communication and… read more here.
Keywords: parameter varying; linear parameter; cross frequency; varying autoregressive ... See more keywords
Message Passing-Based Inference for Time-Varying Autoregressive Models
Sign Up to like & getrecommendations! Published in 2021 at "Entropy"
DOI: 10.3390/e23060683
Abstract: 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… read more here.
Keywords: time varying; time; varying autoregressive; passing based ... See more keywords