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  • 1980-1984  (6)
  • 1982  (6)
  • 1
    Digitale Medien
    Digitale Medien
    Springer
    Journal of optimization theory and applications 36 (1982), S. 263-276 
    ISSN: 1573-2878
    Schlagwort(e): Partial differential equations ; Riccati equations ; successive approximation technique ; comparison theorems ; existence and uniqueness theorems ; optimal sensor location ; fundamental solution
    Quelle: Springer Online Journal Archives 1860-2000
    Thema: Mathematik
    Notizen: Abstract In this paper, we discuss the partial differential equation of Riccati type that describes the optimal filtering error covariance function for a linear distributed-parameter system with pointwise observations. Since this equation contains the Dirac delta function, it is impossible to apply directly the usual methods of functional analysis to prove existence and uniqueness of a bounded solution. By using properties of the fundamental solution and the classical technique of successive approximation, we prove the existence and uniqueness theorem. We then prove the comparison theorem for partial differential equations of Riccati type. Finally, we consider some applications of these theorems to the distributed-parameter optimal sensor location problem.
    Materialart: Digitale Medien
    Standort Signatur Erwartet Verfügbarkeit
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  • 2
    Publikationsdatum: 1982-02-01
    Print ISSN: 0022-3239
    Digitale ISSN: 1573-2878
    Thema: Mathematik
    Publiziert von Springer
    Standort Signatur Erwartet Verfügbarkeit
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  • 3
    facet.materialart.
    Unbekannt
    In:  Other Sources
    Publikationsdatum: 2019-06-28
    Beschreibung: The atmospheric species concentration distribution-estimation problem that arises from the measurement configuration of remote sensing, which involves a field of view that moves across the region, is solved by means of the partial differential equation for atmospheric diffusion and the Wiener-Hopf theory. A numerical study is also undertaken for the estimation of concentration distribution downwind of a hypothetical, continuous ground-level source of pollutants.
    Schlagwort(e): ENVIRONMENT POLLUTION
    Materialart: IEEE Transactions on Geoscience and Remote Sensing; GE-20; Apr. 198
    Format: text
    Standort Signatur Erwartet Verfügbarkeit
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  • 4
    Publikationsdatum: 2019-06-28
    Beschreibung: The problem of the assimilation of remote sensing data into mathematical models of atmospheric pollutant species was investigated. The problem is posed in terms of the matching of spatially integrated species burden measurements to the predicted three dimensional concentration fields from atmospheric diffusion models. General conditions are derived for the "reconstructability' of atmospheric concentration distributions from data typical of remote sensing applications, and a computational algorithm (filter) for the processing of remote sensing data is developed.
    Schlagwort(e): EARTH RESOURCES AND REMOTE SENSING
    Materialart: E83-10159 , NASA-CR-169769 , NAS 1.26:169769
    Format: application/pdf
    Standort Signatur Erwartet Verfügbarkeit
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  • 5
    Publikationsdatum: 2019-06-28
    Beschreibung: The reconstruction of a concentration distribution from spatially averaged and noise-corrupted data is a central problem in processing atmospheric remote sensing data. Distributed parameter observer theory is used to develop reconstructibility conditions for distributed parameter systems having measurements typical of those in remote sensing. The relation of the reconstructibility condition to the stability of the distributed parameter observer is demonstrated. The theory is applied to a variety of remote sensing situations, and it is found that those in which concentrations are measured as a function of altitude satisfy the conditions of distributed state reconstructibility.
    Schlagwort(e): ENVIRONMENT POLLUTION
    Materialart: IEEE Transactions on Automatic Control; AC-27; Feb. 198
    Format: text
    Standort Signatur Erwartet Verfügbarkeit
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  • 6
    Publikationsdatum: 2019-06-28
    Beschreibung: The problem of the assimilation of remote sensing data into mathematical models of atmospheric pollutant species was investigated. The data assimilation problem is posed in terms of the matching of spatially integrated species burden measurements to the predicted three-dimensional concentration fields from atmospheric diffusion models. General conditions were derived for the reconstructability of atmospheric concentration distributions from data typical of remote sensing applications, and a computational algorithm (filter) for the processing of remote sensing data was developed.
    Schlagwort(e): EARTH RESOURCES AND REMOTE SENSING
    Materialart: E83-10062 , NASA-CR-169574 , NAS 1.26:169574
    Format: application/pdf
    Standort Signatur Erwartet Verfügbarkeit
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