Results 41 to 50 of about 1,946,431 (327)
Multitarget Tracking Using One Time Step Lagged Delta-Generalized Labeled Multi-Bernoulli Smoothing
IEEE Access, 2020 Aiming at improving the tracking performance of the delta-generalized labeled multi-Bernoulli (δ-GLMB) filter, we present a one time step lagged δ-GLMB smoother in this work, which also inherently outputs targets trajectories and differs ...
Guolong Liang +3 more
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Smooth forecasting with the smooth package in R
CoRR, 2023 There are many forecasting related packages in R with varied popularity, the most famous of all being \texttt{forecast}, which implements several important forecasting approaches, such as ARIMA, ETS, TBATS and others. However, the main issue with the existing functionality is the lack of flexibility for research purposes, when it comes to modifying the
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Utility Perception in System Dynamics Models
Systems, 2018 The utility perceived by individuals is believed to be different from the utility experienced by that individual. System dynamicists implicitly categorize this phenomenon as a form of bounded rationality, and traditionally employ an exponential smoothing
Saeed P. Langarudi, Isa Bar-On
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Modified Smoothing Algorithm for Tracking Multiple Maneuvering Targets in Clutter
Sensors, 2022 This research work extends the fixed interval smoothing based on the joint integrated track splitting (FIsJITS) filter in the multi-maneuvering-targets (MMT) tracking environment.
Sufyan Ali Memon +5 more
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Frontier Materials & TechnologiesUnsatisfactory quality of the surface layer of additive products, in particular increased surface roughness, prevents the widespread use of electron beam powder bed fusion (EBPBF).
Samat K. Mukanov +3 more
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Revista Brasileira de Engenharia Agrícola e Ambiental, 2003 Este trabalho busca estabelecer procedimentos ótimos para o mapeamento digital da declividade em microbacias com Sistemas de Informação Geográfica (SIG). Através dos testes, avaliaram-se os métodos de geoprocessamento, de acordo com análises de regressão
Márcio de M. Valeriano
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Sharpening Sparse Regularizers via Smoothing
IEEE Open Journal of Signal Processing, 2021 Non-convex sparsity-inducing penalties outperform their convex counterparts, but generally sacrifice the cost function convexity. As a middle ground, we propose the sharpening sparse regularizers (SSR) framework to design non-separable non-convex ...
Abdullah H. Al-Shabili +2 more
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, 2015 Smoothing is an estimation method whereby a classical state (probability distribution for classical variables) at a given time is conditioned on all-time (both past and future) observations.
Guevara, Ivonne, Wiseman, Howard
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Smooth minimization of non-smooth functions [PDF]
Mathematical Programming, 2004 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Optimization viewpoint on Kalman smoothing, with applications to robust and sparse estimation
, 2013 In this paper, we present the optimization formulation of the Kalman filtering and smoothing problems, and use this perspective to develop a variety of extensions and applications.
A Carmi +31 more
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