Publications related to Spectral density estimation

Construction of dynamically-dependent stochastic error models, 2018 IEEE/ION Position, Location and Navigation Symposium (PLANS)

Jan Skaloud, Stéphane Guerrier, Philipp Clausen

Stochastic behavior of an instrument is often analyzed by constructing the Allan (or wavelet) variance signatures from an error signal. For inertial sensors, such a signature is conveniently obtained by recording data at rest. The analysis of this signal w ...

IEEE ION PLANS2018

Methodology And Convergence Rates For Functional Time Series Regression

Victor Panaretos, Tung Huy Pham

The functional linear model extends the notion of linear regression to the case where the response and covariates are iid elements of an infinite-dimensional Hilbert space. The unknown to be estimated is a Hilbert-Schmidt operator, whose inverse is by defi ...

STATISTICA SINICA2018

Wasserstein Distributionally Robust Kalman Filtering

Daniel Kuhn, Viet Anh Nguyen, Soroosh Shafieezadeh Abadeh, Peyman Mohajerin Esfahani

We study a distributionally robust mean square error estimation problem over a nonconvex Wasserstein ambiguity set containing only normal distributions. We show that the optimal estimator and the least favorable distribution form a Nash equilibrium. Despit ...

2018

Multiplexed Middle-Down Mass Spectrometry as a Method for Revealing Light and Heavy Chain Connectivity in a Monoclonal Antibody

Yury Tsybin, Natalia Gasilova, Laure Menin, Anton Kozhinov, Konstantin Nagornov, Luca Fornelli, Kristina Srzentic, Daniel Ayoub

Pairing light and heavy chains in monoclonal antibodies (mAbs) using top-down (TD) or middle-down (MD) mass spectrometry (MS) may complement the sequence information on single chains provided by high-throughput genomic sequencing and bottom-up proteomics, ...

AMER CHEMICAL SOC2018

A Physical Model of Non-stationary Blur in Ultrasound Imaging

Jean-Philippe Thiran, Yves Wiaux, Paul Hurley, Dimitris Perdios, Matthieu Martin Jean-André Simeoni, Marcel Arditi, Adrien Georges Jean Besson

Conventional ultrasound (US) imaging relies on delay-and-sum (DAS) beamforming which retrieves a radio- frequency (RF) image, a blurred estimate of the tissue reflectivity function (TRF). Despite the non-stationarity of the blur induced by propagation effe ...

2018

Optimizing Image Denoising for Long-Range Brillouin Distributed Fiber Sensing

Luc Thévenaz, Marcelo Alfonso Soto Hernandez

Linear and nonlinear two-dimensional image processing approaches are analyzed with the aim of removing noise from data acquired by distributed optical fiber sensors based on Brillouin optical time-domain analysis (BOTDA). The impact of the filter parameter ...

2018

Towards More Accurate Radio Telescope Images

Paul Hurley, Matthieu Martin Jean-André Simeoni, Nezihe Merve Gürel

Radio interferometry usually compensates for high levels of noise in sensor/antenna electronics by throwing data and energy at the problem: observe longer, then store and process it all. We propose instead a method to remove the noise explicitly before ima ...

IEEE2018

Towards Generalized FRI Sampling with an Application to Source Resolution in Radioastronomy

Martin Vetterli, Thierry Blu, Hanjie Pan

It is a classic problem to estimate continuous-time sparse signals, like point sources in a direction-of-arrival problem, or pulses in a time-of-flight measurement. The earliest occurrence is the estimation of sinusoids in time series using Prony's method. ...

Institute of Electrical and Electronics Engineers2017

Spectral methods for multiscale stochastic differential equations

Assyr Abdulle, Grigorios A. Pavliotis

This paper presents a new method for the solution of multiscale stochastic differential equations at the diffusive time scale. In contrast to averaging-based methods, e.g., the heterogeneous multiscale method (HMM) or the equation-free method, which rely o ...

2017

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Spectral density estimation

Construction of dynamically-dependent stochastic error models, 2018 IEEE/ION Position, Location and Navigation Symposium (PLANS)

Methodology And Convergence Rates For Functional Time Series Regression

Wasserstein Distributionally Robust Kalman Filtering

Multiplexed Middle-Down Mass Spectrometry as a Method for Revealing Light and Heavy Chain Connectivity in a Monoclonal Antibody

On the Comparison of Gauge Freedom Handling in Optimization-Based Visual-Inertial State Estimation

A Physical Model of Non-stationary Blur in Ultrasound Imaging

Optimizing Image Denoising for Long-Range Brillouin Distributed Fiber Sensing

Towards More Accurate Radio Telescope Images

Towards Generalized FRI Sampling with an Application to Source Resolution in Radioastronomy

Spectral methods for multiscale stochastic differential equations

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Construction of dynamically-dependent stochastic error models, 2018 IEEE/ION Position, Location and Navigation Symposium (PLANS)

Methodology And Convergence Rates For Functional Time Series Regression

A Physical Model of Non-stationary Blur in Ultrasound Imaging

On the Comparison of Gauge Freedom Handling in Optimization-Based Visual-Inertial State Estimation

Spectral methods for multiscale stochastic differential equations

Towards More Accurate Radio Telescope Images

Towards Generalized FRI Sampling with an Application to Source Resolution in Radioastronomy

Wasserstein Distributionally Robust Kalman Filtering

Multiplexed Middle-Down Mass Spectrometry as a Method for Revealing Light and Heavy Chain Connectivity in a Monoclonal Antibody

Optimizing Image Denoising for Long-Range Brillouin Distributed Fiber Sensing