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Title:

NREL's e-Ca Test: A Scalable, High-Sensitivity Water Permeation Measurement Methodology (Poster)

Description:

A test method is described that uses the resistivity of a Calcium film to detect very small amounts of water permeating through a barrier material.

A test method is described that uses the resistivity of a Calcium film to detect very small amounts of water permeating through a barrier material. Minimize

Year of Publication:

2014-09-15

Subjects:

14 SOLAR ENERGY; 36 MATERIALS SCIENCE

14 SOLAR ENERGY; 36 MATERIALS SCIENCE Minimize

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Title:

Don’t shed tears over breaks

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imaging Mathematical Subject Classification: 93E14, 62G08, 68T45, 49M20, 90C31 This essay deals with ‘discontinuous phenomena ’ in time-series. It is an introduction to, and a brief survey of aspects concerning the concepts of segmentation into ‘smooth ’ pieces on the one hand, and the complementary notion of the identification of jumps, on the ...

imaging Mathematical Subject Classification: 93E14, 62G08, 68T45, 49M20, 90C31 This essay deals with ‘discontinuous phenomena ’ in time-series. It is an introduction to, and a brief survey of aspects concerning the concepts of segmentation into ‘smooth ’ pieces on the one hand, and the complementary notion of the identification of jumps, on the other hand. We restrict ourselves to variational approaches, both in discrete, and in continuous time. They will define ‘filters’, with data as ‘inputs ’ and minimizers of functionals as ‘outputs’. The main example is a particularly simple model, which, for historical reasons, we decided to call the Potts functional. We will argue that it is an appropriate tool for the extraction of the simplest and most basic morphological features from data. This is an attempt to interpret data from a well-defined point of view. It is in contrast to restoration of a true signal- perhaps distorted and degraded by noise- which is not in the main focus of this paper. Minimize

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The Pennsylvania State University CiteSeerX Archives

Year of Publication:

2008-07-17

Source:

http://ibb.gsf.de/preprints/2004/pp04-08.pdf

http://ibb.gsf.de/preprints/2004/pp04-08.pdf Minimize

Document Type:

text

Language:

en

Subjects:

image analysis ; edge preserving smoothing ; variational problems ; epiconvergence ; wavelet shrinkage ; regularization ; nonlinear filters ; Potts model ; Mumford- Shah Functional ; segmentation ; time-series ; fractionation curves ; functional magnetic resonance

image analysis ; edge preserving smoothing ; variational problems ; epiconvergence ; wavelet shrinkage ; regularization ; nonlinear filters ; Potts model ; Mumford- Shah Functional ; segmentation ; time-series ; fractionation curves ; functional magnetic resonance Minimize

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Metadata may be used without restrictions as long as the oai identifier remains attached to it.

Metadata may be used without restrictions as long as the oai identifier remains attached to it. Minimize

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Title:

Complexity penalized sums of squares for time series’: Rigorous analytical results. Schriftenreihe des IBB

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A simple variational approach to the estimation of timeseries is studied in detail and mathematical rigor. The functional in question is a complexity penalized sum of squares. The results include existence, uniqueness, continuous dependence on parameters, and stability, in dependence of parameters and data, of the statistical estimate. 1

A simple variational approach to the estimation of timeseries is studied in detail and mathematical rigor. The functional in question is a complexity penalized sum of squares. The results include existence, uniqueness, continuous dependence on parameters, and stability, in dependence of parameters and data, of the statistical estimate. 1 Minimize

Contributors:

The Pennsylvania State University CiteSeerX Archives

Year of Publication:

2008-07-17

Source:

http://ibb.gsf.de/preprints/2005/pp05-01.pdf

http://ibb.gsf.de/preprints/2005/pp05-01.pdf Minimize

Document Type:

text

Language:

en

Subjects:

complexity penalized variational problems ; Potts model ; edge preserving smoothing ; regularization ; timeseries ; nonlinear filters ; segmentation

complexity penalized variational problems ; Potts model ; edge preserving smoothing ; regularization ; timeseries ; nonlinear filters ; segmentation Minimize

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Metadata may be used without restrictions as long as the oai identifier remains attached to it.

Metadata may be used without restrictions as long as the oai identifier remains attached to it. Minimize

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Title:

Segmentation of Time Series: Parameter Dependence of Blake-Zisserman and Mumford-Shah Functionals and the Transition from Discrete to Continuous

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The paper deals with variational approaches to the segmentation of time series into smooth pieces, but allowing for sharp breaks. In discrete time, the corresponding functionals are of Blake-Zisserman type. Their natural counterpart in continuous time are the Mumford-Shah functionals. Time series which minimise these functionals are proper estim...

The paper deals with variational approaches to the segmentation of time series into smooth pieces, but allowing for sharp breaks. In discrete time, the corresponding functionals are of Blake-Zisserman type. Their natural counterpart in continuous time are the Mumford-Shah functionals. Time series which minimise these functionals are proper estimates or representations of the signals behind recorded data. We focus on consistent behaviour of the functionals and the estimates, as parameters vary or as the sampling rate increases. For each time continuous time series f ∈ L 2 ([0, 1]) we take conditional expectations w.r.t. to σ-algebras generated by finer and finer partitions of the time domain into intervals, and thereby construct a sequence (fn)n∈N of discrete time series. As n increases this amounts to sampling the continuous time series with more and more accuracy. Our main result is consistent behaviour of segmentations w.r.t. to Minimize

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The Pennsylvania State University CiteSeerX Archives

Year of Publication:

2008-07-01

Source:

http://ibb.gsf.de/preprints/2005/pp05-02.pdf

http://ibb.gsf.de/preprints/2005/pp05-02.pdf Minimize

Document Type:

text

Language:

en

Subjects:

Segmentation ; Blake- Zisserman and Mumford- Shah functional ; Γ−Convergence ; Hausdorff- metric

Segmentation ; Blake- Zisserman and Mumford- Shah functional ; Γ−Convergence ; Hausdorff- metric Minimize

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Metadata may be used without restrictions as long as the oai identifier remains attached to it.

Metadata may be used without restrictions as long as the oai identifier remains attached to it. Minimize

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Title:

Segmentation of Time Series: Parameter Dependence of Blake-Zisserman and Mumford-Shah Functionals and the Transition from Discrete to Continuous

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Description:

The paper deals with variational approaches to the segmentation of time series into smooth pieces, but allowing for sharp breaks. In discrete time, the corresponding functionals are of Blake-Zisserman type. Their natural counterpart in continuous time are the Mumford-Shah functionals. Time series which minimise these functionals are proper estim...

The paper deals with variational approaches to the segmentation of time series into smooth pieces, but allowing for sharp breaks. In discrete time, the corresponding functionals are of Blake-Zisserman type. Their natural counterpart in continuous time are the Mumford-Shah functionals. Time series which minimise these functionals are proper estimates or representations of the signals behind recorded data. We focus on consistent behaviour of the functionals and the estimates, as parameters vary or as the sampling rate increases. For each time continuous time series f ∈ L 2 ([0,1]) we take conditional expectations w.r.t. to σ-algebras generated by finer and finer partitions of the time domain into intervals, and thereby construct a sequence (fn)n∈N of discrete time series. As n increases this amounts to sampling the continuous time series with more and more accuracy. Our main result is consistent behaviour of segmentations w.r.t. to Minimize

Contributors:

The Pennsylvania State University CiteSeerX Archives

Year of Publication:

2012-11-14

Source:

http://arxiv.org/pdf/math/0511619v1.pdf

http://arxiv.org/pdf/math/0511619v1.pdf Minimize

Document Type:

text

Language:

en

Subjects:

Segmentation ; Blake- Zisserman and Mumford- Shah functional ; Γ−Convergence ; Hausdorff- metric

Segmentation ; Blake- Zisserman and Mumford- Shah functional ; Γ−Convergence ; Hausdorff- metric Minimize

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Title:

Don’t shed tears over breaks

Author:

Description:

imaging Mathematical Subject Classification: 93E14, 62G08, 68T45, 49M20, 90C31 This essay deals with ‘discontinuous phenomena ’ in time-series. It is an introduction to, and a brief survey of aspects concerning the concepts of segmentation into ‘smooth ’ pieces on the one hand, and the complementary notion of the identification of jumps, on the ...

imaging Mathematical Subject Classification: 93E14, 62G08, 68T45, 49M20, 90C31 This essay deals with ‘discontinuous phenomena ’ in time-series. It is an introduction to, and a brief survey of aspects concerning the concepts of segmentation into ‘smooth ’ pieces on the one hand, and the complementary notion of the identification of jumps, on the other hand. We restrict ourselves to variational approaches, both in discrete, and in continuous time. They will define ‘filters’, with data as ‘inputs ’ and minimizers of functionals as ‘outputs’. The main example is a particularly simple model, which, for historical reasons, we decided to call the Potts functional. We will argue that it is an appropriate tool for the extraction of the simplest and most basic morphological features from data. This is an attempt to interpret data from a well-defined point of view. It is in contrast to restoration of a true signal- perhaps distorted and degraded by noise- which is not in the main focus of this paper. Minimize

Contributors:

The Pennsylvania State University CiteSeerX Archives

Year of Publication:

2008-07-17

Source:

http://ibb.gsf.de/preprints/2004/pp04-08.ps

http://ibb.gsf.de/preprints/2004/pp04-08.ps Minimize

Document Type:

text

Language:

en

Subjects:

image analysis ; edge preserving smoothing ; variational problems ; epiconvergence ; wavelet shrinkage ; regularization ; nonlinear filters ; Potts model ; Mumford- Shah Functional ; segmentation ; time-series ; fractionation curves ; functional magnetic resonance

image analysis ; edge preserving smoothing ; variational problems ; epiconvergence ; wavelet shrinkage ; regularization ; nonlinear filters ; Potts model ; Mumford- Shah Functional ; segmentation ; time-series ; fractionation curves ; functional magnetic resonance Minimize

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Metadata may be used without restrictions as long as the oai identifier remains attached to it.

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Title:

Segmentation of Time Series: Parameter Dependence of Blake-Zisserman and Mumford-Shah Functionals and the Transition from Discrete to Continuous

Author:

Description:

The paper deals with variational approaches to the segmentation of time series into smooth pieces, but allowing for sharp breaks. In discrete time, the corresponding functionals are of Blake-Zisserman type. Their natural counterpart in continuous time are the Mumford-Shah functionals. Time series which minimise these functionals are proper estim...

The paper deals with variational approaches to the segmentation of time series into smooth pieces, but allowing for sharp breaks. In discrete time, the corresponding functionals are of Blake-Zisserman type. Their natural counterpart in continuous time are the Mumford-Shah functionals. Time series which minimise these functionals are proper estimates or representations of the signals behind recorded data. We focus on consistent behaviour of the functionals and the estimates, as parameters vary or as the sampling rate increases. For each time continuous time series f ([0, 1]) we take conditional expectations w.r.t. to #-algebras generated by finer and finer partitions of the time domain into intervals, and thereby construct a sequence (f n ) n#N of discrete time series. As n increases this amounts to sampling the continuous time series with more and more accuracy. Our main result is consistent behaviour of segmentations w.r.t. to variation of parameters and increasing sampling rate. Keywords: Segmentation, Blake - Zisserman and Mumford - Shah functional, #-Convergence, Hausdor# - metric MSC: 49J45, 49J52, 93E14 Contents 1 Minimize

Contributors:

The Pennsylvania State University CiteSeerX Archives

Year of Publication:

2009-04-19

Source:

http://ibb.gsf.de/preprints/2005/pp05-02.ps

http://ibb.gsf.de/preprints/2005/pp05-02.ps Minimize

Document Type:

text

Language:

en

Subjects:

Segmentation ; Blake- Zisserman and Mumford- Shah functional ; Γ−Convergence ; Hausdorff- metric

Segmentation ; Blake- Zisserman and Mumford- Shah functional ; Γ−Convergence ; Hausdorff- metric Minimize

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Metadata may be used without restrictions as long as the oai identifier remains attached to it.

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Title:

Complexity Penalized Sums of Squares for Time Series: Rigorous Analytical Results

Author:

Description:

A simple variational approach to the estimation of timeseries is studied in detail and mathematical rigor. The functional in question is a complexity penalized sum of squares. The results include existence, uniqueness, continuous dependence on parameters, and stability, in dependence of parameters and data, of the statistical estimate.

A simple variational approach to the estimation of timeseries is studied in detail and mathematical rigor. The functional in question is a complexity penalized sum of squares. The results include existence, uniqueness, continuous dependence on parameters, and stability, in dependence of parameters and data, of the statistical estimate. Minimize

Contributors:

The Pennsylvania State University CiteSeerX Archives

Year of Publication:

2009-04-19

Source:

http://ibb.gsf.de/preprints/2005/pp05-01.ps

http://ibb.gsf.de/preprints/2005/pp05-01.ps Minimize

Document Type:

text

Language:

en

Subjects:

complexity penalized variational problems ; Potts model ; edge preserving smoothing ; regularization ; timeseries ; nonlinear filters ; segmentation

complexity penalized variational problems ; Potts model ; edge preserving smoothing ; regularization ; timeseries ; nonlinear filters ; segmentation Minimize

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Title:

Complexity Penalised M-Estimation: Fast Computation

Author:

Description:

We present fast algorithms for the exact computation of estimators for time series, based on a simple variational approach. The functionals behind are complexity penalised loglikelihood- or M-functions. We emphasize optimisation simultaneously in all model parameters. The algorithms cover a broad range of estimators, including all those commonly...

We present fast algorithms for the exact computation of estimators for time series, based on a simple variational approach. The functionals behind are complexity penalised loglikelihood- or M-functions. We emphasize optimisation simultaneously in all model parameters. The algorithms cover a broad range of estimators, including all those commonly adopted in the literature. This is illustrated by a series of examples. 1 Minimize

Contributors:

The Pennsylvania State University CiteSeerX Archives

Year of Publication:

2008-07-01

Source:

http://ibb.gsf.de/preprints/2006/pp06-16.pdf

http://ibb.gsf.de/preprints/2006/pp06-16.pdf Minimize

Document Type:

text

Language:

en

Subjects:

complexity penalised variational problems ; Potts model ; edge preserving smoothing ; regularisation ; timeseries ; nonlinear filters ; segmentation

complexity penalised variational problems ; Potts model ; edge preserving smoothing ; regularisation ; timeseries ; nonlinear filters ; segmentation Minimize

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Title:

Focussed Ion Beam Preparation for the Nanoscopic Study of Disintegrated Microfossils

Author:

Year of Publication:

2005

Source:

Geophysical Research Abstracts, Vol. 7, 02417, 2005 ; 2nd General Assembly European Geosciences Union (Vienna, Austria 2005)#

Geophysical Research Abstracts, Vol. 7, 02417, 2005 ; 2nd General Assembly European Geosciences Union (Vienna, Austria 2005)# Minimize

Document Type:

ConferencePaper

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