Results 111 to 120 of about 9,957 (160)
PhotonicsThe spatially modulated full-polarization imaging system encodes complete polarization information into a single interferogram, enabling rapid demodulation.
Ziyang Zhang +12 more
doaj +1 more source
Support in R for state space estimation via Kalman filtering was limited to one package, until fairly recently. In the last five years, the situation has changed with no less than four additional packages offering general implementations of the Kalman ...
Fernando Tusell
core
Parallelised Gaussian mixture filtering for vehicular traffic flow estimation. [PDF]
, 2009 Large traffic network systems require handling huge amounts of data, often distributed over a large geographical region in space and time. Centralised processing is not then the right choice in such cases. In this paper we develop a parallelised Gaussian
Gning, Amadou +3 more
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Fresnel filtering of Gaussian beams in microcavities
, 2011 We study the output from the modes described by the superposition of Gaussian beams confined in the quasistadium microcavities. We experimentally observe the deviation from Snell's law in the output when the incident angle of the Gaussian beam at the ...
Fukushima, T. +5 more
core +1 more source
Inference for Adaptive Time Series Models: Stochastic Volatility and Conditionally Gaussian State Space Form [PDF]
In this paper we replace the Gaussian errors in the standard Gaussian, linear state space model with stochastic volatility processes. This is called a GSSF-SV model.
Neil Shephard, Charles S. Bos
core
Gaussian-Based Robust Filtering for Estimating Engineering Surfaces
, 2002 This paper analyses the shortcomings of Gaussian filtering in practical engineering surface evaluation, introduces robust estimation theory, and proposes a new robust algorithm based on Gaussian filtering, which eliminates the influence of surface ...
Li, Zhu, Jiang, Xiangqian, Li, Huifen
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Gaussian Filters for Nonlinear Filtering Problems
, 1999 In this paper we develop and analyze real-time and accurate filters for nonlinear filtering problems based on the Gaussian distributions. We present the systematic formulation of Gaussian filters and develop efficient and accurate numerical integration ...
Kazufumi Ito, Kaiqi Xiong
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Understanding the Kalman Filter: an Object Oriented Programming Perspective. [PDF]
The basic ideals underlying the Kalman filter are outlined in this paper without direct recourse to the complex formulae normally associated with this method. The novel feature of the paper is its reliance on a new algebraic system based on the first two
Snyder, R.D., Forbes, C.S.
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Vehicle detection and tracking using homography-based plane rectification and particle filtering
, 2010 This paper presents a full system for vehicle detection and tracking in non-stationary settings based on computer vision. The method proposed for vehicle detection exploits the geometrical relations between the elements in the scene so that moving ...
Salgado Álvarez de Sotomayor, Luis +2 more
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Gaussian Sum Particle Filtering For Dynamic State Space Models
, 2001 For dynamic systems, sequential Bayesian estimation requires updating of the filtering and predictive densities. For nonlinear and non-Gaussian models, sequential updating is not as straightforward as in the linear Gaussian model.
Jayesh Kotecha And +2 more
core