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A well-known complete multi-channel equalization technique aiming at acoustic system inversion is the multiple-input/output inverse theorem (MINT -based technique [19], which however suffers froMINT -based in practechnique
In this paper the idea of input reconstruction by means of system inversion is discussed.
In this paper, an iterative learning control approach, clean system inversion, is proposed for multi-input multi-output (MIMO) time-invariant systems, as a remedy to the system inversion law.
The paper addresses this estimation problem based on systematic methods for nonlinear system inversion and filtering resulting in efficient estimators.
In this paper a Matlab-based toolbox for the input-output system inversion of linear systems is presented.
The feedforward control is calculated through system inversion of a multi-body system utilizing its differentially flatness.
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We show that it is possible to address this problem by relying on a system-inversion-based fault estimation filter that is parameterized using identified Markov parameters.
Through support for massively parallel solvers and interfaces for high-performance computing (HPC) systems, inversions with thousands of seismic traces and billions of model parameters can be performed.
In this system, waveform inversion is carried out in the frequency domain to reduce the computational time.
The objective of this study was to explore the potential of combining observations on surface soil moisture and crop variables – leaf area index (LAI) and above-ground biomass for estimating soil parameters (water holding capacity and soil depth) in a two-layered soil system using inversion of the crop model STICS.
The theory for resonant second-harmonic generation in systems with inversion symmetry has been outlined according to a scheme of microscopic nonlocal response, where the internal field and induced polarization are determined self-consistently.
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