Physically motivated rank constraint on direct throughput of state-space models
Sign Up to like & getrecommendations! Published in 2018 at "IFAC-PapersOnLine"
DOI: 10.1016/j.ifacol.2018.09.156
Abstract: In frequency range vibration testing a few outside band eigenmodes are often included in the system identification to compensate for residual mass and stiffness influences. It has been observed that, in particular, energy conjugate input-output… read more here.
Keywords: state; space models; direct throughput; state space ... See more keywords
Likelihood ratio testing in linear state space models: An application to dynamic stochastic general equilibrium models
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Econometrics"
DOI: 10.1016/j.jeconom.2020.04.029
Abstract: Abstract This paper considers the problem of hypothesis testing in linear Gaussian state space models. We consider two hypotheses of interest: a simple null and a hypothesis of explicit parameter restrictions. We derive the asymptotic… read more here.
Keywords: state; state space; likelihood ratio; testing linear ... See more keywords
Drilling head knives degradation modelling based on stochastic diffusion processes backed up by state space models
Sign Up to like & getrecommendations! Published in 2022 at "Mechanical Systems and Signal Processing"
DOI: 10.1016/j.ymssp.2021.108448
Abstract: Abstract System quality requirements are typically formed by consideration of reliability and safety performance. Failures caused by system weakness, degradation or fatigue may cause undesired, and potentially dangerous, consequences. For various reasons, not all processes… read more here.
Keywords: degradation; system; state space; diffusion processes ... See more keywords
State Estimation for a Class of Piecewise Affine State-Space Models
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Signal Processing Letters"
DOI: 10.1109/lsp.2016.2633624
Abstract: We propose a filter for piecewise affine state-space models. In each filtering recursion, the true filtering posterior distribution is a mixture of truncated normal distributions. The proposed filter approximates the mixture with a single normal… read more here.
Keywords: state; state space; affine state; piecewise affine ... See more keywords
Particle-Based Adaptive-Lag Online Marginal Smoothing in General State-Space Models
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Signal Processing"
DOI: 10.1109/tsp.2019.2941066
Abstract: We present a novel algorithm, an adaptive-lag smoother, approximating efficiently, in an online fashion, sequences of expectations under the marginal smoothing distributions in general state-space models. The algorithm evolves recursively a bank of estimators, one… read more here.
Keywords: adaptive lag; general state; marginal smoothing; state space ... See more keywords
Sparse Bayesian Estimation of Parameters in Linear-Gaussian State-Space Models
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Signal Processing"
DOI: 10.1109/tsp.2023.3278867
Abstract: State-space models (SSMs) are a powerful statistical tool for modelling time-varying systems via a latent state. In these models, the latent state is never directly observed. Instead, a sequence of data points related to the… read more here.
Keywords: state; state space; space; linear gaussian ... See more keywords
Autoregressive Point Processes as Latent State-Space Models: A Moment-Closure Approach to Fluctuations and Autocorrelations
Sign Up to like & getrecommendations! Published in 2018 at "Neural Computation"
DOI: 10.1162/neco_a_01121
Abstract: Modeling and interpreting spike train data is a task of central importance in computational neuroscience, with significant translational implications. Two popular classes of data-driven models for this task are autoregressive point-process generalized linear models (PPGLM)… read more here.
Keywords: autoregressive point; latent state; state space; moment closure ... See more keywords
Reproducible parallel inference and simulation of stochastic state space models using odin, dust, and mcstate
Sign Up to like & getrecommendations! Published in 2020 at "Wellcome Open Research"
DOI: 10.12688/wellcomeopenres.16466.2
Abstract: State space models, including compartmental models, are used to model physical, biological and social phenomena in a broad range of scientific fields. A common way of representing the underlying processes in these models is as… read more here.
Keywords: space models; model; inference; state space ... See more keywords
Quantitative evaluation of radiodermatitis following whole-breast radiotherapy with various color space models: A feasibility study
Sign Up to like & getrecommendations! Published in 2022 at "PLoS ONE"
DOI: 10.1371/journal.pone.0264925
Abstract: Purpose We analyzed skin images with various color space models to objectively assess radiodermatitis severity in patients receiving whole-breast radiotherapy. Methods Twenty female patients diagnosed with breast cancer were enrolled prospectively. All patients received whole-breast… read more here.
Keywords: color space; space; radiotherapy; radiodermatitis ... See more keywords