Sök i SwePub databas

  Utökad sökning

Träfflista för sökning "LAR1:lu ;pers:(Gustafsson Mats);pers:(Soldovieri Francesco)"

Sökning: LAR1:lu > Gustafsson Mats > Soldovieri Francesco

  • Resultat 1-7 av 7
Sortera/gruppera träfflistan
  • Nordebo, Sven, et al. (författare)
  • Data fusion for electromagnetic and electrical resistive tomography based on maximum likelihood
  • 2011
  • Ingår i: International Journal of Geophysics. - Hindawi. - 1687-885X. ; :Article ID 617089, s. 1-11
  • Tidskriftsartikel (refereegranskat)abstract
    • This paper presents a maximum likelihood based approach to data fusion for electromagnetic (EM) and electrical resistive (ER) tomography. The statistical maximum likelihood criterion is closely linked to the additive Fisher information measure, and it facilitates an appropriate weighting of the measurement data which can be useful with multi-physics inverse problems. The Fisher information is particularly useful for inverse problems which can be linearized similar to the Born approximation. In this paper, a proper scalar productis dened for the measurements and a truncated Singular Value Decomposition (SVD) based algorithm is devised which combines the measurement data of the two imaging modalities in a way that is optimal in the sense of maximum likelihood. As a multi-physics problem formulation with applications in geophysics, the problem of tunnel detection based on EM and ER tomography is studied in this paper. To illustrate the connection between the Green's functions, the gradients and the Fisher information, two simple and generic forward models are described in detail regarding two-dimensional EM and ER tomography, respectively. Numerical examples are included to illustrate the potential impact of an imbalance between the singular values and the variance of the measurement noise when dierent imaging modalities are incorporated in the inversion. The examples furthermore illustrate the signicance of taking a statistically based weighting of the measurement data into proper account.
  • Nordebo, Sven, et al. (författare)
  • Data fusion for reconstruction algorithms via different sensors in geophysical sensing
  • 2011
  • Ingår i: Journal of Geophysics and Engineering. - IOP Publishing Ltd. - 1742-2132. ; 8:3, s. S54-S60
  • Tidskriftsartikel (refereegranskat)abstract
    • Information fusion via multimodal inverse problems and different sensors is addressed using a Fisher information analysis approach. The Fisher information measure is inherently additive, and it facilitates an appropriate weighting of the measurement data that is statistically optimal and can hence be useful with reconstruction algorithms in geophysical sensing. Given that there exists proper knowledge about the sensor noise statistics, correlations and spectral contents, as well as a correct forward model, the Fisher information is a natural measure of information because it is closely linked to the statistical maximum likelihood principle. To illustrate the concept of data correlation based on statistical Fisher information analysis, two simple and generic examples are employed in electrical resistivity and electromagnetic tomography, which are motivated by geophysical applications, such as tunnel detection. The examples demonstrate that a properly weighted data fusion can be of crucial importance for an ill-posed multimodal inverse problem.
  • Nordebo, Sven, et al. (författare)
  • Fisher information analysis in electrical impedance tomography
  • 2013
  • Ingår i: Journal of Geophysics and Engineering. - Institute of Physics (IOP). - 1742-2132. ; 10:6
  • Tidskriftsartikel (refereegranskat)abstract
    • This paper provides a quantitative analysis of the optimal accuracy and resolution in electrical impedance tomography (EIT) based on the Cramér–Rao lower bound. The imaging problem is characterized by the forward operator and its Jacobian. The Fisher information operator is defined for a deterministic parameter in a real Hilbert space and a stochastic measurement in a finite-dimensional complex Hilbert space with a Gaussian measure. The connection between the Fisher information and the singular value decomposition (SVD) based on the maximum likelihood (ML) criterion (the ML-based SVD) is established. It is shown that the eigenspaces of the Fisher information provide a suitable basis to quantify the trade-off between the accuracy and the resolution of the (nonlinear) inverse problem. It is also shown that the truncated ML-based pseudo-inverse is a suitable regularization strategy for a linearized problem, which exploits sufficient statistics for estimation within these subspaces. The statistical-based Cramér–Rao lower bound provides a complement to the deterministic upper bounds and the L-curve techniques that are employed with linearized inversion. To this end, electrical impedance tomography provides an interesting example where the eigenvalues of the SVD usually do not exhibit a very sharp cut-off, and a trade-off between the accuracy and the resolution may be of practical importance. A numerical study of a hypothetical EIT problem is described, including a statistical analysis of the model errors due to the linearization.
  • Proto, Monica, et al. (författare)
  • Transport Infrastructure Surveillance and Monitoring by Electromagnetic Sensing
  • 2010
  • Ingår i: Sensors. - 1424-8220. ; 10:12, s. 10620-10639
  • Tidskriftsartikel (refereegranskat)abstract
    • The ISTIMES project, funded by the European Commission in the frame of a joint Call "ICT and Security" of the Seventh Framework Programme, is presented and preliminary research results are discussed. The main objective of the ISTIMES project is to design, assess and promote an Information and Communication Technologies (ICT)-based system, exploiting distributed and local sensors, for non-destructive electromagnetic monitoring of critical transport infrastructures. The integration of electromagnetic technologies with new ICT information and telecommunications systems enables remotely controlled monitoring and surveillance and real time data imaging of the critical transport infrastructures. The project exploits different non-invasive imaging technologies based on electromagnetic sensing (optic fiber sensors, Synthetic Aperture Radar satellite platform based, hyperspectral spectroscopy, Infrared thermography, Ground Penetrating Radar-, low-frequency geophysical techniques, Ground based systems for displacement monitoring). In this paper, we show the preliminary results arising from the GPR and infrared thermographic measurements carried out on the Musmeci bridge in Potenza, located in a highly seismic area of the Apennine chain (Southern Italy) and representing one of the test beds of the project.
Skapa referenser, mejla, bekava och länka
  • Resultat 1-7 av 7
pil uppåt Stäng

Kopiera och spara länken för att återkomma till aktuell vy