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Learning Generative State Space Models for Active Inference [PDF]
Frontiers in Computational Neuroscience, 2020 In this paper we investigate the active inference framework as a means to enable autonomous behavior in artificial agents. Active inference is a theoretical framework underpinning the way organisms act and observe in the real world.
Ozan Çatal +4 more
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Statistical analysis of organelle movement using state-space models [PDF]
Plant Methods, 2023 Background Organelle motility is essential for the correct cellular function of various eukaryotic cells. In plant cells, chloroplasts move towards the intracellular area irradiated by a weak light to maximise photosynthesis. To initiate this process, an
Haruki Nishio +2 more
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Parameter and State Estimator for State Space Models [PDF]
The Scientific World Journal, 2014 This paper proposes a parameter and state estimator for canonical state space systems from measured input-output data. The key is to solve the system state from the state equation and to substitute it into the output equation, eliminating the state ...
Ruifeng Ding, Linfan Zhuang
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Quantifying spontaneous infant movements using state-space models [PDF]
Scientific ReportsOver the first few months after birth, the typical emergence of spontaneous, fidgety general movements is associated with later developmental outcomes.
E. Passmore +6 more
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Parameter-coupled state space models based on quasi-Gaussian fuzzy approximation [PDF]
Scientific ReportsThe accuracy of a fuzzy system’s approximation is closely tied to the performance of fuzzy control systems design, while this system’s interpretability depends on the description of a mechanical model using human language.
Yizhi Wang +5 more
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Advancing brain-machine interfaces: Moving beyond linear state space models [PDF]
Frontiers in Systems Neuroscience, 2015 Advances in recent years have dramatically improved output control by Brain-Machine Interfaces (BMIs). Such devices nevertheless remain robotic and limited in their movements compared to normal human motor performance.
Adam G Rouse +5 more
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Identification State Space models and some Time Series models [PDF]
المجلة العراقية للعلوم الاحصائية, 2021 In this research, a comparison of the identification process for time series models represented by ARIMA models was studied by identification several models and choosing the best model based on some statistical criteria and one of the dynamic models ...
Zina Asem, heyam Hayawi
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dynamichazard: Dynamic Hazard Models Using State Space Models
Journal of Statistical Software, 2021 The dynamichazard package implements state space models that can provide a computationally efficient way to model time-varying parameters in survival analysis. I cover the models and some of the estimation methods implemented in dynamichazard, apply them
Benjamin Christoffersen
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Wavelets in state space models [PDF]
Applied Stochastic Models in Business and Industry, 2003 AbstractIn this paper, we consider the utilization of wavelets in conjunction with state space models. Specifically, the parameters in the system matrix are expanded in wavelet series and estimated via the Kalman Filter and the EM algorithm. In particular this approach is used for switching models.
Zandonade, Eliana, Morettin, Pedro A.
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Predictive Control Based upon State Space Models [PDF]
Modeling, Identification and Control, 1989 Repetitive online computation of the control vector by solving the optimal control problem of a non-linear multivariable process with arbitrary performance indices is investigated.
Jens G. Balchen +2 more
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