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SEG Technical Program Expanded Abstracts 1992, 1992
Amplitude variation with offset (AVO) analysis is sensitive to errors in the moveout correction. To reduce moveout errors, AVO‐effects are estimated using time windows. For each time window, block‐NMO is used to avoid NMO‐stretch, and correction for residual NMO is performed by an iterative cross‐correlation technique.
Bjørn Ursin, Bjørn Olav Ekren
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Amplitude variation with offset (AVO) analysis is sensitive to errors in the moveout correction. To reduce moveout errors, AVO‐effects are estimated using time windows. For each time window, block‐NMO is used to avoid NMO‐stretch, and correction for residual NMO is performed by an iterative cross‐correlation technique.
Bjørn Ursin, Bjørn Olav Ekren
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2009 30th IEEE Real-Time Systems Symposium, 2009
A key feature of control systems is robustness, the property that small perturbations in the system inputs cause only small changes in its outputs. Robustness is key to designing systems that work under uncertain or imprecise environments. While continuous control design algorithms can explicitly incorporate robustness as a design goal, it is not clear
Rupak Majumdar, Indranil Saha
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A key feature of control systems is robustness, the property that small perturbations in the system inputs cause only small changes in its outputs. Robustness is key to designing systems that work under uncertain or imprecise environments. While continuous control design algorithms can explicitly incorporate robustness as a design goal, it is not clear
Rupak Majumdar, Indranil Saha
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Robust Procedures in Multivariate Analysis II. Robust Canonical Variate Analysis
Applied Statistics, 1982SUMMARY Robust M-estimation for canonical variate analysis is developed, based on a functional relationship model; the associated weights depend on the distance of an observation from the canonical variate mean for the group. For uncontaminated data, the robust Mestimation procedure performs similarly to the usual canonical variate analysis.
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2005
We provide an overview of robust Bayesian analysis with emphasis on foundational, decision oriented and computational approaches. Common types of robustness analyses are described, including global and local sensitivity analysis and loss and likelihood robustness.
Fabrizio Ruggeri +2 more
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We provide an overview of robust Bayesian analysis with emphasis on foundational, decision oriented and computational approaches. Common types of robustness analyses are described, including global and local sensitivity analysis and loss and likelihood robustness.
Fabrizio Ruggeri +2 more
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Proceedings of IEEE Conference on Computer Vision and Pattern Recognition CVPR-94, 1994
We develop a new robust algorithm for the estimation of optic flow and extraction of other motion-relevant information. A novel combination of the Hough Transform, and robust statistical methods results in unbiased estimates for multiple motions, parallel segmentation and estimation and increased robustness to noise and changes of illumination.
null Bober, null Kittler
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We develop a new robust algorithm for the estimation of optic flow and extraction of other motion-relevant information. A novel combination of the Hough Transform, and robust statistical methods results in unbiased estimates for multiple motions, parallel segmentation and estimation and increased robustness to noise and changes of illumination.
null Bober, null Kittler
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2003
In the previous chapters the stability property of a given time-delay system was studied. In engineering applications, it is now very common that one does not know exactly the system under investigation; that is, the system contains some elements (blocks) that are uncertain.
Keqin Gu +2 more
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In the previous chapters the stability property of a given time-delay system was studied. In engineering applications, it is now very common that one does not know exactly the system under investigation; that is, the system contains some elements (blocks) that are uncertain.
Keqin Gu +2 more
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2013
Robust control deals explicitly with system uncertainty and how it affects the design of control systems. By dealing with the real parameter uncertainties in control systems we can identify the critical subset of the uncertain parameter set over which the stability will be violated. The analysis depends how system uncertainty is represented.
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Robust control deals explicitly with system uncertainty and how it affects the design of control systems. By dealing with the real parameter uncertainties in control systems we can identify the critical subset of the uncertain parameter set over which the stability will be violated. The analysis depends how system uncertainty is represented.
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Communications in Statistics - Simulation and Computation, 2016
CoPlot analysis is one of the multivariate data-visualizing techniques. It consists of two graphs: the first one represents the distribution of p-dimensional observations over two-dimensional space, whereas the second shows the relations of variables with the observations.
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CoPlot analysis is one of the multivariate data-visualizing techniques. It consists of two graphs: the first one represents the distribution of p-dimensional observations over two-dimensional space, whereas the second shows the relations of variables with the observations.
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2003
Textures are one of the basic features in visual searching and computer vision. In the research literature, most of the attention has been focussed on the texture features with minimal consideration of the noise models. In this chapter we investigate the problem of texture classification from a maximum likelihood perspective.
Nicu Sebe, Michael S. Lew
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Textures are one of the basic features in visual searching and computer vision. In the research literature, most of the attention has been focussed on the texture features with minimal consideration of the noise models. In this chapter we investigate the problem of texture classification from a maximum likelihood perspective.
Nicu Sebe, Michael S. Lew
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