Results 1 to 10 of about 54,368 (115)
Gaussian Filters for Nonlinear Filtering Problems [PDF]
IEEE Transactions on Automatic Control, 2000 The most widely used filter to estimate the state of a nonlinear stochastic system from noisy observation data is the extended Kalman filter. However, if the nonlinearities are significant, its performance can be considerably improved as recent works by Alspace and Sorenson (1967, 1972), C. P. Fang, Julier and Uhlmann (1994, 1995) have shown.
Kazufumi K. Ito, K Xiong
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A Review of Nonlinear Filtering Algorithms in Integrated Navigation Systems [PDF]
SensorsBotao Wang, Jiaqian Si
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Communications in Information and Systems, 2006 A discrete time filter is constructed where both the observation and signal process have non-linear dynamics with additive white Gaussian noise. Using the reference probably frame- work a convolution Zakai equation is obtained which updates the unnormalized conditional density.
Elliott, Robert J., Haykin, Simon
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Signal Processing, 2015 The paper discusses a novel sub-class of linear-in-the-parameters nonlinear filters, the Legendre nonlinear filters. The novel sub-class combines the best characteristics of truncated Volterra filters and of the recently introduced even mirror Fourier nonlinear filters, in particular: (i) Legendre nonlinear filters can arbitrarily well approximate any ...
Alberto Carini +3 more
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Poisson's Equation in Nonlinear Filtering [PDF]
SIAM Journal on Control and Optimization, 2014 The aim of this paper is to provide a variational interpretation of the nonlinear filter in continuous time. A time-stepping procedure is introduced, consisting of successive minimization problems in the space of probability densities. The weak form of the nonlinear filter is derived via analysis of the first-order optimality conditions for these ...
Richard S. Laugesen +3 more
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Nonlinear filtering with transfer operator [PDF]
2013 American Control Conference, 2013 This paper presents a new nonlinear filtering algorithm that is shown to outperform state-of-the-art particle filters with resampling. Starting from the Itˆo stochastic differential equation, the proposed algorithm harnesses Karhunen- Lo'eve expansion to derive an approximate non-autonomous dynamical system, for which transfer operator based density ...
Dutta, Parikshit +2 more
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The Hitchhiker’s guide to nonlinear filtering
Journal of Mathematical Psychology, 2020 Nonlinear filtering is used in online estimation of a dynamic hidden variable from incoming data and has vast applications in different fields, ranging from engineering, machine learning, economic science and natural sciences. We start our review of the theory on nonlinear filtering from the simplest ‘filtering’ task we can think of, namely static ...
Kutschireiter, Anna +2 more
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On nonlinear filter generators [PDF]
, 1997 In this paper the bits in a linear feedback shift register are treated as if they were independent random variables. A necessary condition for filter functions which result in independent random output bits is given. An example shows that the sufficient condition given by Golic in [2] is not necessary.
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Information geometric nonlinear filtering [PDF]
Infinite Dimensional Analysis, Quantum Probability and Related Topics, 2015 This paper develops information geometric representations for nonlinear filters in continuous time. The posterior distribution associated with an abstract nonlinear filtering problem is shown to satisfy a stochastic differential equation on a Hilbert information manifold. This supports the Fisher metric as a pseudo-Riemannian metric.
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A differential geometric approach to nonlinear filtering: the projection filter [PDF]
IEEE Transactions on Automatic Control, 1998 This paper provides an introduction to projection filters (PF) in the case of probability densities in exponential families. Filters are derived using the geometric approach. Some numerical simulations are given for the cubic sensor problem.
Brigo, Damiano +2 more
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