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20152022
most citedMinimax state estimates for abstract Neumann problems

4 citations · 9 across the 9 of their papers we have counts for

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6 papers · 1 filter

math.OC2018

Non-Uniform Stability, Detectability, and, Sliding Mode Observer Design for Time Varying Systems with Unknown Inputs

Markus Tranninger, Sergiy Zhuk, Martin Steinberger +2

This paper discusses stability and robustness properties of a recently proposed observer algorithm for linear time varying systems. The observer is based on the approximation and s…

math.OC20171 cited

Exponentially convergent data assimilation algorithm for Navier-Stokes equations

Jason Frank, Tigran Tchrakian, Sergiy Zhuk

The paper presents a new state estimation algorithm for a bilinear equation representing the Fourier- Galerkin (FG) approximation of the Navier-Stokes (NS) equations on a torus in…

math.OC2017

Localised sequential state estimation for advection dominated flows with non-Gaussian uncertainty description

Emanuele Ragnoli, Mykhaylo Zayats, Fearghal O'Donncha +1

This paper presents a new iterative state estimation algorithm for advection dominated flows with non-Gaussian uncertainty description of -type: uncertain initial conditi…

math.OC20174 cited

Minimax state estimates for abstract Neumann problems

Alexander Nakonechnyi, Sergiy Zhuk

The paper presents analytic expressions of minimax (worst-case) estimates for solutions of linear abstract Neumann problems in Hilbert space with uncertain (not necessarily bounded…

math.OC20172 cited

Where computer vision can aid physics: dynamic cloud motion forecasting from satellite images

Sergiy Zhuk, Tigran Tchrakian, Albert Akhriev +2

This paper describes a new algorithm for solar energy forecasting from a sequence of Cloud Optical Depth (COD) images. The algorithm is based on the following simple observation: t…

math.OC2015

General Optimization Framework for Robust and Regularized 3D Full Waveform Inversion

Stephen Becker, Lior Horesh, Aleksandr Aravkin +1

Scarcity of hydrocarbon resources and high exploration risks motivate the development of high fidelity algorithms and computationally viable approaches to exploratory geophysics. W…