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See detailStationary Wavelet Transform for denoising Pulsed Thermography data: optimization of wavelet parameters for enhancing defects detection
Revel, Gian Marco; Copertaro, Edoardo UL; Chiariotti, Paolo et al

in Quantitative Infra Red Thermography Journal (2017)

Innovative denoising techniques based on Stationary Wavelet Transform (SWT) have started being applied to Pulsed Thermography (PT) sequences, showing marked potentialities in improving defect detection ... [more ▼]

Innovative denoising techniques based on Stationary Wavelet Transform (SWT) have started being applied to Pulsed Thermography (PT) sequences, showing marked potentialities in improving defect detection. In this contribution, a SWT-based denoising procedure is performed on high and low resolution PT sequences. Samples under test are two composite panels with known defects. The denoising procedure undergoes an optimization step. An innovative criterion for selecting the optimal decomposition level in multi-scale SWT-based denoising is proposed. The approach is based on a comparison, in the wavelet domain, of the information content in the thermal image with noise propagated. The optimal wavelet basis is selected according to two performance indexes, respectively based on the probability distribution of the information content of the denoised frame, and on the Energy-to-Shannon Entropy ratio. After the optimization step, denoising is applied on the whole thermal sequence. The approximation coefficients at the optimal level are moved to the frequency domain, then low-pass filtered. Linear Minimum Mean Square Error (LMMSE) is applied to detail coefficients at the optimal level. Finally, Pulsed Phase Thermography (PPT) is performed. The performance of the optimized denoising method in improving the defect detection capability respect to the non-denoised case is quantified using the Contrast Noise Ratio (CNR) criterion. [less ▲]

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See detailStatische und dynamische Zustandsbewertung von Stahlbetonbauteilen
Bungard, Volker UL; Waldmann, Danièle UL

in Abstract book of 51. Forschungskolloquium des Deutschen Ausschusses für Stahlbetonbau (2010)

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See detailStatistical Analysis of Calcium Oscillations
Skupin, Alexander UL; Falcke, Martin

in European Physical Journal. Special Topics (2010), 187

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See detailStatistical Analysis of Dead-time System using a Deterministic Equivalent Modeling Method
Duong, Pham UL

in Asia-Pacific Journal of Chemical Engineering (2011), 6(2), 369378

To increase precision and reliability of automatic control systems, random factors affecting the controlsystem have to be taken into account. In this article, the deterministic equivalent modelling method ... [more ▼]

To increase precision and reliability of automatic control systems, random factors affecting the controlsystem have to be taken into account. In this article, the deterministic equivalent modelling method (DEMM) is used for statistical analysis of time delay systems with random parameters. The proposed method is compared with several existing methods such as the Monte Carlo, Latin-Hypercube, and Quasi Monte Carlo method, to demonstrate its validity and effectiveness. The result shows that the proposed DEMM-based approach drastically reduces computational time with a desired accuracy over traditional methods. [less ▲]

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See detailStatistical Analysis of Piglet Stillbirth
Canario, L.; Cantoni, E.; Le Bihan, Etienne UL et al

Scientific Conference (2006, August)

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See detailStatistical Analysis of the Global Geodesic Function for 3D Object Classification
Aouada, Djamila UL; Feng, Shuo; Krim, Hamid

in IEEE International Conference on Acoustics, Speech and Signal Processing, 2007. ICASSP 2007 (2007)

This paper presents a novel classification strategy for 3D objects. Our technique is based on using a global geodesic function to intrinsically describe the surface of an object. The choice of the global ... [more ▼]

This paper presents a novel classification strategy for 3D objects. Our technique is based on using a global geodesic function to intrinsically describe the surface of an object. The choice of the global geodesic function ensures the invariance of the classification procedure to scaling and all isometric transformations. Using the Jensen-Shannon divergence, feature parameters are extracted from the probability distribution functions of the global geodesic function for each one of the classes. These parameters are used in the decision of a class membership of an object. This approach demonstrates low computational cost, efficiency, and robustness to resolution over many different data sets. [less ▲]

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See detailStatistical Comparison and Combination of GPS, GLONASS, and Multi-GNSS Multipath Reflectometry Applied to Snow Depth Retrieval
Tabibi, Sajad UL; Geremia-Nievinski, Felipe; van Dam, Tonie UL

in IEEE Transactions on Geoscience and Remote Sensing (2017), (99),

Global navigation satellite system (GNSS) multipath reflectometry (MR) has emerged as a new technique that uses signals of opportunity broadcast by GNSS satellites and tracked by ground-based receivers to ... [more ▼]

Global navigation satellite system (GNSS) multipath reflectometry (MR) has emerged as a new technique that uses signals of opportunity broadcast by GNSS satellites and tracked by ground-based receivers to retrieve environmental variables such as snow depth. The technique is based on the simultaneous reception of direct or line-of-sight (LOS) transmissions and corresponding coherent surface reflections (non-LOS). Until recently, snow depth retrieval algorithms only used legacy and modernized GPS signals. Using multiple GNSS constellations for reflectometry would improve GNSS-MR applications by providing more observations from more satellites and independent signals (carrier frequencies and code modulations). We assess GPS and GLONASS for combined multi-GNSS-MR using simulations as well as field measurements. Synthetic observations for different signals indicated a lack of detectable interfrequency and intercode biases in GNSS-MR snow depth retrievals. Received signals from a GNSS station continuously operating in France for a two-winter period are used for experimental snow depth retrieval. We perform an internal validation of various GNSS signals against the proven GPS-L2-C signal, which was validated externally against in situ snow depth in previous studies. GLONASS observations required a more complex handling to account for topography because of its particular ground track repeatability. Signal intercomparison show an average correlation of 0.922 between different GPS snow depths and GPS-L2-CL, while GLONASS snow depth retrievals have an average correlation that exceeds 0.981. In terms of precision and accuracy, legacy GPS signals are worse, while GLONASS signals and modernized GPS signals are of comparable quality. Finally, we show how an optimal multi-GNSS combined daily snow depth time series can be formed employing variance factors with a ~59%-90% precision improvement compared to individual signal snow depth retrievals, resulting in snow depth retrieval with uncertainty of 1.3 cm. The developed combination strategy can also be applied for the European Galileo and the Chines BeiDou navigation systems. [less ▲]

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See detailStatistical extraction of process zones and representative subspaces in fracture of random composites
Kerfriden, P.; Schmidt, K. M.; Rabczuk, T. et al

in International Journal for Multiscale Computational Engineering (2013), 11(3), 253-287

We propose to identify process zones in heterogeneous materials by tailored statistical tools. The process zone is redefined as the part of the structure where the random process cannot be correctly ... [more ▼]

We propose to identify process zones in heterogeneous materials by tailored statistical tools. The process zone is redefined as the part of the structure where the random process cannot be correctly approximated in a low-dimensional deterministic space. Such a low-dimensional space is obtained by a spectral analysis performed on precomputed solution samples. A greedy algorithm is proposed to identify both process zone and low-dimensional representative subspace for the solution in the complementary region. In addition to the novelty of the tools proposed in this paper for the analysis of localized phenomena, we show that the reduced space generated by the method is a valid basis for the construction of a reduced-order model. © 2013 by Begell House, Inc. [less ▲]

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See detailStatistical Framework for Optimization in the Multi-User MIMO Uplink With ZF-DFE
Järmyr, Simon; Ottersten, Björn UL; Jorswieck, Eduard A.

in IEEE Transactions on Signal Processing (2014), 62(10), 2730-2745

We consider performance optimization in the uplink of a multiuser multiantenna communication system. Each user multiplexes data onto several independently encoded data streams, which are spatially ... [more ▼]

We consider performance optimization in the uplink of a multiuser multiantenna communication system. Each user multiplexes data onto several independently encoded data streams, which are spatially precoded and conveyed over a fading narrowband multiple-input multiple-output (MIMO) channel. All users' data streams are decoded successively at the receiving base station using zero-forcing decision feedback equalization (ZF-DFE). We target the joint optimization of a decoding order and linear precoders for all users based on long-term channel information. For a class of general MIMO channel models, including the separable-correlation and double-scattering models, we show that the choice of precoder for a certain user does not affect the performance of the others. This leads to a particularly straightforward characterization of general user utility regions as a polyblock, or a convex polytope if time-sharing is allowed. We formulate the decoding-ordering problem under transmit-correlated Rayleigh fading as a linear assignment problem, enabling the use of existing efficient algorithms. Combining decoding ordering with single-user precoder optimization by means of alternating optimization, we propose an efficient iterative scheme that is verified numerically to converge fast and perform close to optimally, successfully reaping the benefits of both precoding and ordering in the MIMO uplink. [less ▲]

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See detailStatistical inference for Vasicek-type model driven by Hermite processes
Nourdin, Ivan UL; Tran, Thi Thanh Diu UL

in Stochastic Processes and Their Applications (2019), 129(10), 3774-3791

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See detailStatistical Precoding and Detection Ordering in MIMO Multiple-Access Channels with Decision Feedback Equalization
Järmyr, Simon; Ottersten, Björn UL; Jorswieck, Eduard

in Communications (ICC), 2011 IEEE International Conference on (2011)

We present a novel approach for joint transmitter-receiver design in the uplink of a wireless multiple-input multiple-output communication system. It applies to, e.g., a fast-fading frequency-division ... [more ▼]

We present a novel approach for joint transmitter-receiver design in the uplink of a wireless multiple-input multiple-output communication system. It applies to, e.g., a fast-fading frequency-division duplexing system with periodic pilot signaling from each user - a scenario hindering transmitter optimization based on channel state information (CSI), while CSI-based receiver optimization is possible. Each user multiplexes data onto several, independently coded subchannels processed by a linear precoder, and detected at a base station (BS) employing zero-forcing decision feedback (DF) equalization, eliminating all interference prior to detection. We target the problem of jointly designing fixed linear precoders for all users as well as a fixed detection order for the DF receiver based on long-term channel statistics. We propose an efficiently implementable alternating-minimization technique that is verified numerically to converge fast, and to outperform the popular V-BLAST scheme - a computationally more complex ordered-DF receiver with limited applicability by requiring equal-rate subchannels in the system. [less ▲]

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See detailStatistical Precoding with Decision Feedback Equalization over a Correlated MIMO Channel
Järmyr, Simon; Ottersten, Björn UL; Eduard, Jorswieck

in IEEE Transactions on Signal Processing (2010), 58(12), 6298-6311

The decision feedback (DF) transceiver, combining linear precoding and DF equalization, can establish point-to-point communication over a wireless multiple-input multiple-output channel. Matching the DF ... [more ▼]

The decision feedback (DF) transceiver, combining linear precoding and DF equalization, can establish point-to-point communication over a wireless multiple-input multiple-output channel. Matching the DF-transceiver design parameters to the channel characteristics can improve system performance, but requires channel knowledge. We consider the fast-fading channel scenario, with a receiver capable of tracking the channel-state variations accurately, while the transmitter only has long-term, channel-distribution information. The receiver design problem given channel-state information is well studied in the literature. We focus on transmitter optimization, which amounts to designing a statistical precoder to assist the channel-tailored DF equalizer. We develop a design framework that encompasses a wide range of performance metrics. Common cost functions for precoder optimization are analyzed, thereby identifying a structure of typical cost functions. Transmitter design is approached for typical cost functions in general, and we derive a precoder design formulation as a convex optimization problem. Two important subclasses of cost functions are considered in more detail. First, we explore a symmetry of DF transceivers with a uniform subchannel rate allocation, and derive a simplified convex optimization problem, which can be efficiently solved even as system dimensions grow. Second, we explore the tractability of a certain class of mean square error based cost functions, and solve the transmitter design problem with a simple algorithm that identifies the convex hull of a set of points in R2. The behavior of DF transceivers with optimal precoders is investigated by numerical means. [less ▲]

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See detailStatistical properties and information content of calcium oscillations.
Skupin, Alexander UL; Falcke, Martin

in Genome informatics. International Conference on Genome Informatics (2007), 18

Calcium is the most important second messenger in living cells serving as a critical link between a large variety of extracellular stimuli and the intracellular target. Often, the Ca(2+) signal is carried ... [more ▼]

Calcium is the most important second messenger in living cells serving as a critical link between a large variety of extracellular stimuli and the intracellular target. Often, the Ca(2+) signal is carried by [Ca(2+)] oscillations. Our recent studies have demonstrated that in contrast to traditional ideas Ca(2+) oscillations do not occur by simple synchronization of channel clusters opening and closing in an oscillatory fashion but originate from microscopic fluctuation caused by the stochastic binding of the ligands Ca(2+) and IP(3) to the receptor's binding sites. They are orchestrated spatially on the cell level by wave nucleation. In this paper we analyze the stochastic data and show how internal properties can be determined from global observations. Further, we analyze the information content of spontaneous and stimulated oscillations. [less ▲]

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See detailStatistical shape analysis for the classification of renal tumors affecting children
Schiltz, Jang UL; Giebel, Stefan; Schenk, Jens-Peter

in Pakistan Journal of Statistics (2013), 29(1), 129-138

In this research project, we describe an application of statistical shape analysis. In order to differentiate the various kidney tumours appearing in childhood we use shape analysis on two-dimensional ... [more ▼]

In this research project, we describe an application of statistical shape analysis. In order to differentiate the various kidney tumours appearing in childhood we use shape analysis on two-dimensional magnetic resonance images (MRI). We show that this mathematical procedure can be an interesting tool to assist the radiologist who is required to make a decision based on their intuition and their experience in lack of specific tumour characteristics. This study is the first one using MR images in oncology for statistical shape analysis. Our method is innovative in the way to find suitable landmarks and to test the differences, even if the sample size is small. In order to test the mean shape, the statistical test of Ziezold is used. [less ▲]

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See detailStatistical significance of trends in Zenith Wet Delay from re-processed GPS solutions
Klos, Anna; Hunegnaw, Addisu UL; Teferle, Felix Norman UL et al

in GPS Solutions (2018)

Long series of Zenith Wet Delay (ZWD) obtained as part of a homogeneous re-processing of Global Positioning System solutions constitute a reliable set of data to be assimilated into climate models. The ... [more ▼]

Long series of Zenith Wet Delay (ZWD) obtained as part of a homogeneous re-processing of Global Positioning System solutions constitute a reliable set of data to be assimilated into climate models. The correct stochastic properties, i.e. the noise model of these data, have to be identified to assess the real value of ZWD trend uncertainties since assuming an inappropriate noise model may lead to over- or underestimated error bounds leading to statistically insignificant trends. We present the ZWD time series for 1995–2017 for 120 selected globally distributed stations. The deterministic model in the form of a trend and significant seasonal signals were removed prior to the noise analysis. We examined different stochastic models and compared them to widely assumed white noise (WN). A combination of the autoregressive process of first-order plus WN (AR(1) + WN) was proven to be the preferred stochastic representation of the ZWD time series over the generally assumed white-noise-only approach. We found that for 103 out of 120 considered stations, the AR(1) process contributed to the AR(1) + WN model in more than 50% with noise amplitudes between 9 and 68 mm. As soon as the AR(1) + WN model was employed, 43 trend estimates became statistically insignificant, compared to 5 insignificant trend estimates for a white-noise-only model. We also found that the ZWD trend uncertainty may be underestimated by 5–14 times with median value of 8 using the white-noise-only assumption. Therefore, we recommend that AR(1) + WN model is employed before tropospheric trends are to be determined with the greatest reliability. [less ▲]

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See detailA Statistical View on Calcium Oscillations.
Powell, Jake; Falcke, Martin; Skupin, Alexander UL et al

in Advances in experimental medicine and biology (2020), 1131

Transient rises and falls of the intracellular calcium concentration have been observed in numerous cell types and under a plethora of conditions. There is now a growing body of evidence that these whole ... [more ▼]

Transient rises and falls of the intracellular calcium concentration have been observed in numerous cell types and under a plethora of conditions. There is now a growing body of evidence that these whole-cell calcium oscillations are stochastic, which poses a significant challenge for modelling. In this review, we take a closer look at recently developed statistical approaches to calcium oscillations. These models describe the timing of whole-cell calcium spikes, yet their parametrisations reflect subcellular processes. We show how non-stationary calcium spike sequences, which e.g. occur during slow depletion of intracellular calcium stores or in the presence of time-dependent stimulation, can be analysed with the help of so-called intensity functions. By utilising Bayesian concepts, we demonstrate how values of key parameters of the statistical model can be inferred from single cell calcium spike sequences and illustrate what information whole-cell statistical models can provide about the subcellular mechanistic processes that drive calcium oscillations. In particular, we find that the interspike interval distribution of HEK293 cells under constant stimulation is captured by a Gamma distribution. [less ▲]

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See detailA Statistically Efficient Estimator for Co-array Based DoA Estimation
Sedighi, Saeid UL; Shankar, Bhavani UL; Ottersten, Björn UL

Poster (2018, October)

Co-array-based Direction of Arrival (DoA) estimation using Sparse linear arrays (SLAs) has recently gained considerable interest in array processing due to the attractive capability of providing enhanced ... [more ▼]

Co-array-based Direction of Arrival (DoA) estimation using Sparse linear arrays (SLAs) has recently gained considerable interest in array processing due to the attractive capability of providing enhanced degrees of freedom. Although a variety of estimators have been suggested in the literature for co-array-based DoA estimation, none of them are statistically efficient. This work introduces a novel Weighted Least Squares (WLS) estimator for the co-array-based DoA estimation employing the covariance fitting method. Then, an optimal weighting is given so that the asymptotic performance of the proposed WLS estimator coincides with the Cram\'{e}r-Rao Bound (CRB), thereby ensuring statistical efficiency of resulting WLS estimator. This implies that the proposed WLS estimator has significantly better performance compared to existing methods in the literature. Numerical simulations are provided to corroborate the asymptotic statistical efficiency and the improved performance of the proposed estimator. [less ▲]

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See detailStatistics of Colloidal Suspensions Stirred by Microswimmers
Ortlieb, Levke; Rafai, Salima; Peyla, Philippe et al

in Physical Review Letters (2019), 122(14),

We present a statistical analysis of the experimental trajectories of colloids in a dilute suspension of the green algae Chlamydomonas reinhardtii. The measured probability density function (pdf) of the ... [more ▼]

We present a statistical analysis of the experimental trajectories of colloids in a dilute suspension of the green algae Chlamydomonas reinhardtii. The measured probability density function (pdf) of the displacements of colloids covers 7 orders of magnitude. The pdfs are characterized by non-Gaussian tails for intermediate time intervals, but nevertheless they collapse when scaled with their standard deviation. This diffusive scaling breaks down for longer time intervals and the pdf becomes Gaussian. However, the mean squared displacements of tracer positions are linear over the complete measurement time interval. Experiments are performed for various tracer diameters, swimmer concentrations, and mean swimmer velocities. This allows a rigorous comparison with several theoretical models. We can exclude a description based on an effective temperature and other mean field approaches that describe the irregular motion as a sum of the fluctuating far field of many microswimmers. The data are best described by the microscopic model by J.-L. Thiffeault, Distribution of particle displacements due to swimming microorganisms, Phys. Rev. E 92, 023023 (2015). [less ▲]

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See detailStatistische Mechanik harter Stäbchen
Schilling, Tanja UL

Presentation (2006, November 10)

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See detailThe Status of GNSS Data Processing Systems to Estimate Integrated Water Vapour for Use in Numerical Weather Prediction Models
Ahmed, Furqan UL; Teferle, Felix Norman UL; Bingley, Richard et al

in Willis, Pascal; Rizos, Chris (Eds.) IAG 150 Years Proceedings of the 2013 IAG Scientific Assembly, Postdam,Germany, 1–6 September, 2013 (2016)

Modern Numerical Weather Prediction (NWP) models make use of the GNSS-derived Zenith Total Delay (ZTD) or Integrated Water Vapour (IWV) estimates to enhance the quality of their forecasts. Usually, the ... [more ▼]

Modern Numerical Weather Prediction (NWP) models make use of the GNSS-derived Zenith Total Delay (ZTD) or Integrated Water Vapour (IWV) estimates to enhance the quality of their forecasts. Usually, the ZTD is assimilated into the NWP models on 3-hourly to 6-hourly intervals but with the advancement of NWP models towards higher update rates e.g. 1-hourly cycling in the Rapid update Cycle (RUC) NWP, it has become of high interest to estimate ZTD on sub-hourly intervals. In turn, this imposes requirements related to the timeliness and accuracy of the ZTD estimates and has lead to a development of various strategies to process GNSS observations to obtain ZTD with different latencies and accuracies. Using present GNSS products and tools, ZTD can be estimated in realtime (RT), near real-time (NRT) and post-processing (PP) modes. The aim of this study is to provide an overview and accuracy assessment of various RT, NRT, and PP IWV estimation systems and comparing their achieved accuracy with the user requirements for GNSS meteorology. The NRT systems are based on Bernese GPS Software 5.0 and use a double-differencing strategy whereas the PP system is based on the Bernese GNSS Software 5.2 using the precise point positioning (PPP) strategy. The RT systems are based on the BKG Ntrip Client 2.7 and the PPP-Wizard both using PPP. The PPP-Wizard allows integer ambiguity resolution at a single station and therefore the effect of fixing integer ambiguities on ZTD estimates will also be presented. [less ▲]

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