Book ChapterDOI
Subspace Estimation with Uncertain and Correlated Data
M. Muhlich
- pp 353-372
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TLDR
A new method for improving total least squares (TLS) based estimation with suitably chosen weights is presented and it will be shown how to compute them for general noise models.Citations
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Statistical optimization for geometric computation : theory and practice
TL;DR: In this article, the authors propose a general theory iterative estimation scheme effective gradient approximation reduction from the klaman filter estimation from linear hypotheses for 3-D reconstruction of points.
Journal ArticleDOI
Generalized coorbit theory, Banach frames, and the relation to α-modulation spaces
TL;DR: In this article, it was shown that the general theory applied to the affine Weyl-Heisenberg group gives rise to families of smoothness spaces that can be identified with α-modulation spaces.
Journal ArticleDOI
Adaptive Frame Methods for Elliptic Operator Equations: The Steepest Descent Approach
TL;DR: By using three basic subroutines an implementable, convergent scheme can be derived, which, moreover, has optimal computational complexity and is based on adaptive steepest descent iterations.
Journal ArticleDOI
Distances of Time Series Components by Means of Symbolic Dynamics
TL;DR: A simple method for visualizing time-dependent similarities and dissimilarities between the components of a high-dimensional time series via the obtained pattern type distributions and approximate them in a one-dimensional manner is described.
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Adaptive metrics in the nearest neighbours method
TL;DR: It is shown, that this modified metrics is advantageous in prediction in comparison with standard Euclidean metrics or weighted metrics, which is able to adjust its parameters to each segment of a time series.
References
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Book
Multiple view geometry in computer vision
Richard Hartley,Andrew Zisserman +1 more
TL;DR: In this article, the authors provide comprehensive background material and explain how to apply the methods and implement the algorithms directly in a unified framework, including geometric principles and how to represent objects algebraically so they can be computed and applied.
Multiple View Geometry in Computer Vision.
TL;DR: This book is referred to read because it is an inspiring book to give you more chance to get experiences and also thoughts and it will show the best book collections and completed collections.
Book
The Total Least Squares Problem: Computational Aspects and Analysis
TL;DR: This paper presents a meta-analyses of the relationships between total least squares estimation and classical linear regression in Multicollinearity problems and some of the properties of these relationships are explained.
Numerically Stable Direct Least Squares Fitting of Ellipses
TL;DR: This paper presents a numerically stable non-iterative algorithm for fitting an ellipse to a set of data points based on a least squares minimization which leads to a simple, stable and robust fitting method which can be easily implemented.
Book
Statistical Optimization for Geometric Computation: Theory and Practice
TL;DR: This text for graduate students discusses the mathematical foundations of statistical inference for building three-dimensional models from image and sensor data that contain noise--a task involving autonomous robots guided by video cameras and sensors.
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