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Autonomous tracking and state estimation with generalized group lasso
We address the problem of autonomous tracking and state estimation for marine vessels,
autonomous vehicles, and other dynamic signals under a (structured) sparsity assumption …
autonomous vehicles, and other dynamic signals under a (structured) sparsity assumption …
Variable splitting methods for constrained state estimation in partially observed Markov processes
In this letter, we propose a class of efficient, accurate, and general methods for solving state-
estimation problems with equality and inequality constraints. The methods are based on …
estimation problems with equality and inequality constraints. The methods are based on …
Taylor moment expansion for continuous-discrete Gaussian filtering and smoothing
The paper is concerned with non-linear Gaussian filtering and smoothing in continuous-
discrete state-space models, where the dynamic model is formulated as an It\^{o} stochastic …
discrete state-space models, where the dynamic model is formulated as an It\^{o} stochastic …
Augmented sigma-point Lagrangian splitting method for sparse nonlinear state estimation
Nonlinear state estimation using Bayesian filtering and smoothing is still an active area of
research, especially when sparsity-inducing regularization is used. However, even the latest …
research, especially when sparsity-inducing regularization is used. However, even the latest …