LAUSR

About LAUSR
Donate
Contact Us

Follow us:

You are not signed in:

Sign Up!


   Articles with "space models" as a keyword



Physically motivated rank constraint on direct throughput of state-space models

Sign Up to like & get
recommendations! 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 & get
recommendations! 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
Photo from wikipedia

Drilling head knives degradation modelling based on stochastic diffusion processes backed up by state space models

Sign Up to like & get
recommendations! 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

Quantifying spontaneous infant movements using state-space models

Sign Up to like & get
recommendations! Published in 2024 at "Scientific Reports"

DOI: 10.1038/s41598-024-80202-x

Abstract: Over the first few months after birth, the typical emergence of spontaneous, fidgety general movements is associated with later developmental outcomes. In contrast, the absence of fidgety movements is a core feature of several neurodevelopmental… read more here.

Keywords: movements using; infant; space models; state space ... See more keywords

Estimating mixed-effects state-space models via particle filters and the EM algorithm

Sign Up to like & get
recommendations! Published in 2024 at "Journal of Statistical Computation and Simulation"

DOI: 10.1080/00949655.2024.2337339

Abstract: In this paper, we focus on studying the Mixed-Effects State-Space (MESS) models previously introduced by Liu et al. [Liu D, Lu T, Niu X-F, et al. Mixed-effects state-space models for analysis of longitudinal dynamic systems.… read more here.

Keywords: effects state; mixed effects; space models; state space ... See more keywords

CNN-based plant disease recognition using colour space models

Sign Up to like & get
recommendations! Published in 2024 at "International Journal of Image and Data Fusion"

DOI: 10.1080/19479832.2023.2300335

Abstract: ABSTRACT The growing population increases the demand for agricultural production. Owing to some plant diseases, this production is continuously decreasing. Detecting and recognising these diseases at the initial stage is crucial for the sake of… read more here.

Keywords: plant; recognition; colour space; cnn based ... See more keywords
Photo from wikipedia

State Estimation for a Class of Piecewise Affine State-Space Models

Sign Up to like & get
recommendations! 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 & get
recommendations! 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 & get
recommendations! 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

Neural Memory State Space Models for Medical Image Segmentation

Sign Up to like & get
recommendations! Published in 2024 at "International journal of neural systems"

DOI: 10.1142/s0129065724500680

Abstract: With the rapid advancement of deep learning, computer-aided diagnosis and treatment have become crucial in medicine. UNet is a widely used architecture for medical image segmentation, and various methods for improving UNet have been extensively… read more here.

Keywords: state space; space models; medical image; image segmentation ... See more keywords

Autoregressive Point Processes as Latent State-Space Models: A Moment-Closure Approach to Fluctuations and Autocorrelations

Sign Up to like & get
recommendations! 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