Results 121 to 130 of about 9,957 (160)
Applying Dual-Kalman Filtering Algorithm to Radar Estimation Systems
, 2012 [[abstract]]Target Maneuvering situations are usually occurred in radar target tracking systems. Tracking maneuvering targets in a radar system is complicated because it can not directly measure target accelerations.
Chung, Yi-Nung; Juang, D. J. ; Chuang, K. C.
core
Statistical Software for State Space Methods
In this paper we review the state space approach to time series analysis and establish the notation that is adopted in this special volume of the Journal of Statistical Software.
Jacques J. F. Commandeur +2 more
core
Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications, 2015 Murata, Masaya +2 more
openaire +2 more sources
Some of the next articles are maybe not open access.
Related searches:
Related searches:
The Switching Hierarchical Gaussian Filter
2021 IEEE International Symposium on Information Theory (ISIT), 2021In this paper we discuss variational message passing-based (VMP) inference in a switching Hierarchical Gaussian Filter (HGF). An HGF is a flexible hierarchical state space model that supports closed-form VMP-based approximate inference for tracking of both states and slowly time-varying parameters. Since natural signals often submit to regime-switching
Ismail Senöz +4 more
openaire +1 more source
Proceedings of 13th International Conference on Pattern Recognition, 1996
A multiscale region detector for low-level image analysis is described. The basis of the detector is a set of filters similar to the Laplacian of an elliptical Gaussian. The responses of these filters to ideal ellipses are derived, and equations for determining the parameters of detected ellipses from the filter responses are found.
Scott A. Jackson, Narendra Ahuja
openaire +1 more source
A multiscale region detector for low-level image analysis is described. The basis of the detector is a set of filters similar to the Laplacian of an elliptical Gaussian. The responses of these filters to ideal ellipses are derived, and equations for determining the parameters of detected ellipses from the filter responses are found.
Scott A. Jackson, Narendra Ahuja
openaire +1 more source
Proceedings of the 11th IEEE Signal Processing Workshop on Statistical Signal Processing (Cat. No.01TH8563), 2002
Sequential Bayesian estimation for dynamic state space models involves recursive estimation of hidden states based on noisy observations. The update of filtering and predictive densities for nonlinear models with non-Gaussian noise using Monte Carlo particle filtering methods is considered.
Jayesh H. Kotecha, Petar M. Djuric
openaire +1 more source
Sequential Bayesian estimation for dynamic state space models involves recursive estimation of hidden states based on noisy observations. The update of filtering and predictive densities for nonlinear models with non-Gaussian noise using Monte Carlo particle filtering methods is considered.
Jayesh H. Kotecha, Petar M. Djuric
openaire +1 more source
Gaussian-Adaptive Bilateral Filter
IEEE Signal Processing Letters, 2020Recent studies have demonstrated that a bilateral filter can increase the quality of edge-preserving image smoothing significantly. Different strategies or mechanisms have been used to eliminate the brute-force computation in bilateral filters. However, blindly decreasing the processing time of the bilateral filter cannot further ameliorate the ...
Bo-Hao Chen, Yi-Syuan Tseng, Jia-Li Yin
openaire +1 more source
2015
Modern databases tailored to highly distributed, fault tolerant management of information for big data applications exploit a classical data structure for reducing disk and network I/O as well as for managing data distribution: The Bloom filter. This data structure allows to encode small sets of elements, typically the keys in a key-value store, into a
Martin Werner 0001, Mirco Schönfeld
openaire +1 more source
Modern databases tailored to highly distributed, fault tolerant management of information for big data applications exploit a classical data structure for reducing disk and network I/O as well as for managing data distribution: The Bloom filter. This data structure allows to encode small sets of elements, typically the keys in a key-value store, into a
Martin Werner 0001, Mirco Schönfeld
openaire +1 more source
Gaussian Filtering With Cyber-Attacked Data [PDF]
IEEE Signal Processing LettersGaussian filtering is a commonly used nonlinear filtering method. This letter proposes an advanced Gaussian filtering method for handling cyber-attacked measurement data.
Guddu Kumar +2 more
exaly +2 more sources
A quasi-Gaussian Kalman filter
2006 American Control Conference, 2006In this paper, we present a Gaussian approximation to the nonlinear filtering problem, namely the quasi-Gaussian Kalman filter. Starting with the recursive Bayes filter, we invoke the Gaussian approximation to reduce the filtering problem into an optimal Kalman recursion.
Suman Chakravorty +2 more
openaire +1 more source