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Modeling Univariate and Multivariate Stochastic Volatility in R with stochvol and factorstochvol
Journal of Statistical Software, 2021 Stochastic volatility (SV) models are nonlinear state-space models that enjoy increasing popularity for fitting and predicting heteroskedastic time series.
Darjus Hosszejni, Gregor Kastner
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Bellman Filtering for State-Space Models [PDF]
SSRN Electronic Journal, 2020 This article presents a filter for state-space models based on Bellman's dynamic programming principle applied to the mode estimator. The proposed Bellman filter generalises the Kalman filter including its extended and iterated versions, while remaining equally inexpensive computationally.
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TIME-VARIANT MODEL OF HEAT-AND-MASS EXCHANGE FOR STEAM HUMIDIFIER
Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska, 2020 The dynamical model of heat-mass exchange for a steam humidifier with lumped parameters, which can be used for synthesis of control systems by inflowing-exhaust ventilation installations, or industrial complexes of artificial microclimate, is considered.
Igor Golinko, Volodymyr Drevetskiy
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Frontiers in Energy Research, 2022 The Cummins equation is commonly applied to describe the motion of floating structures. Because of the convolution term, the efficiency of calculation is low and the error accumulation problems in numerical integration calculation are serious.
Li Wei +6 more
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On the State-Space Model of Unawareness
, 2023 working paper, please reference this version in further ...
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Non-linear optimal control for multi-DOF electro-hydraulic robotic manipulators
IET Cyber-systems and Robotics, 2020 A non-linear optimal (H-infinity) control approach is proposed for the dynamic model of multi-degree-of-freedom (DOF) electro-hydraulic robotic manipulators.
Gerasimos Rigatos +4 more
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A Meson Binding State Model in Two-Dimensional Space
ParticlesIn this paper, we first show that the four masses of the Upsilon binding states—namely, Y(1S) through Y(4S)—composed of bottom quarks and anti-bottom quarks follow logarithmic spacing. The correlation coefficient R between the experimental values and the
Yasushi Muraki, Shoichi Shibata
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Posterior Analysis of State Space Model with Spherical Symmetricity
Journal of Probability and Statistics, 2015 The present work investigates state space model with nonnormal disturbances when the deviation from normality has been observed only with respect to kurtosis and the distribution of disturbances continues to follow a symmetric family of distributions ...
Ranjita Pandey
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TrackingMamba: Visual State Space Model for Object Tracking
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingIn recent years, UAV object tracking has provided technical support across various fields. Most existing work relies on convolutional neural networks (CNNs) or visual transformers.
Qingwang Wang +6 more
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Advances in Neural Information Processing Systems 37Recent State Space Models (SSMs) such as S4, S5, and Mamba have shown remarkable computational benefits in long-range temporal dependency modeling. However, in many sequence modeling problems, the underlying process is inherently modular and it is of interest to have inductive biases that mimic this modular structure.
Jindong Jiang +4 more
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