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Related papers: Consistency Bands for divergences measures

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First principle based prediction of mean flow quantities of wall-bounded turbulent flows (channel, pipe, and turbulent boundary layer - TBL) is of great importance from both physics and engineering standpoints. Here (Part I), we present a…

Fluid Dynamics · Physics 2015-05-12 Zhen-Su She , Xi Chen , Fazle Hussain

Consider the scattering of the two- or three-dimensional Helmholtz equation where the source of the electric current density is assumed to be compactly supported in a ball. This paper concerns the stability analysis of the inverse source…

Analysis of PDEs · Mathematics 2016-07-26 Peijun Li , Ganghua Yuan

In this paper, we study the asymptotic stability of two wave equations coupled by velocities of anti-symmetric type via only one damping. We adopt the frequency domain method to prove that the system with smooth initial data is…

Analysis of PDEs · Mathematics 2020-11-24 Yan Cui , Zhiqiang Wang

When data do not conform to the hypothesis of a known sampling-variance, the fitting of a constant to the set of measured values is a long debated problem. Given the data, the fitting would require to find which measurand value is most…

Data Analysis, Statistics and Probability · Physics 2011-09-27 Giovanni Mana , Maria Mirabela Predescu

The number of times that we can access a system to extract information via quantum metrology is always finite, and possibly small, and realistic amounts of prior knowledge tend to be moderate. Thus theoretical consistency demands a…

Quantum Physics · Physics 2021-12-02 Jesús Rubio

The paper treats density measures as typical examples of finitely additive measures in $\mathbb{R}^n$. We study their structure and derive basic properties. In addition, estimates for related integrals are provided. The results are applied…

Analysis of PDEs · Mathematics 2026-03-26 Moritz Schönherr , Friedemann Schuricht

We develop a general method for calculating statistical properties of the speckle pattern of coherent waves propagating in disordered media. In some aspects this method is similar to the Boltzmann-Langevin approach for the calculation of…

Mesoscale and Nanoscale Physics · Physics 2011-09-12 Oded Agam , A. V. Andreev , B. Spivak

In this paper we provide new methodology for inference of the geometric features of a multivariate density in deconvolution. Our approach is based on multiscale tests to detect significant directional derivatives of the unknown density at…

Methodology · Statistics 2016-11-21 Konstantin Eckle , Nicolai Bissantz , Holger Dette

Anomalies are strange data points; they usually represent an unusual occurrence. Anomaly detection is presented from the perspective of Wireless sensor networks. Different approaches have been taken in the past, as we will see, not only to…

Machine Learning · Computer Science 2017-08-30 Pelumi Oluwasanya

A density ratio is defined by the ratio of two probability densities. We study the inference problem of density ratios and apply a semi-parametric density-ratio estimator to the two-sample homogeneity test. In the proposed test procedure,…

Machine Learning · Statistics 2010-10-26 Takafumi Kanamori , Taiji Suzuki , Masashi Sugiyama

We establish a link between stability estimates for a hyperbolic inverse problem via the Boundary Control method and the blowup of a constant appearing in the contexts of optimal unique continuation and cost of approximate controllability.

Analysis of PDEs · Mathematics 2025-03-11 Spyridon Filippas , Lauri Oksanen

Measurement error and disturbance, in the presence of conservation laws, are analysed in general operational terms. We provide novel quantitative bounds demonstrating necessary conditions under which accurate or non-disturbing measurements…

Quantum Physics · Physics 2023-06-07 M. Hamed Mohammady , Takayuki Miyadera , Leon Loveridge

In this paper, we establish uniform asymptotic certainty bands for the conditional cumulative distribution function. To this aim, we give exact rate of strong uniform consistency for the local linear estimator of this function. The…

Statistics Theory · Mathematics 2014-07-21 Sandie Ferrigno , Bernard Foliguet , Myriam Maumy-Bertrand , Aurélie Muller-Gueudin

Quantifying how distinguishable two stochastic processes are lies at the heart of many fields, such as machine learning and quantitative finance. While several measures have been proposed for this task, none have universal applicability and…

Statistical Mechanics · Physics 2020-07-01 Chengran Yang , Felix C. Binder , Mile Gu , Thomas J. Elliott

Most time series observed in practice exhibit time-varying trend (first-order) and autocovariance (second-order) behaviour. Differencing is a commonly-used technique to remove the trend in such series, in order to estimate the time-varying…

Methodology · Statistics 2022-09-07 Euan T. McGonigle , Rebecca Killick , Matthew A. Nunes

Characteristic scale is a notion that pervades the geophysical sciences, but it has no widely accepted precise definition. The wavelet transform decomposes a time series into coefficients that are associated with different scales. The…

Methodology · Statistics 2010-07-26 Michael J. Keim , Donald B. Percival

Simple rules of thumb are derived for the precision with which s-wave and p-wave thresholds can be determined by a series of equally spaced cross section mesasurements near threshold. Backgrounds and beam spreads are ignored.

High Energy Physics - Experiment · Physics 2007-05-23 Robert N. Cahn

Nonlinearity in many systems is heavily dependent on component variation and environmental factors such as temperature. This is often overcome by keeping signals close enough to the device's operating point that it appears approximately…

Signal Processing · Electrical Eng. & Systems 2022-05-18 Lachlan J. Gunn , Andrew Allison , Derek Abbott

We investigate the average coherence with respect to a complete set of complementary measurements. By using a Wigner-Yanase skew information-based coherence measure introduced in [Phys. Rev. A \textbf{96}, 022130, 2017], we evaluate the…

Quantum Physics · Physics 2019-08-13 Bin Chen , Shao-Ming Fei

A general divergence measure for monotonic functions is introduced. Its connections with the f-divergence for convex functions are explored. The main properties are pointed out.

Probability · Mathematics 2007-05-23 Sever Silvestru Dragomir
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