Ιδρυματικό Αποθετήριο
Πολυτεχνείο Κρήτης
EN  |  EL

Αναζήτηση

Πλοήγηση

Ο Χώρος μου

Non-parametric Identification of anisotropic (Elliptic) correlations in spatially distributed data sets

Chorti Arsenia, Christopoulos Dionysios

Απλή Εγγραφή


URIhttp://purl.tuc.gr/dl/dias/E18AEC51-5D0C-44A2-9A6C-070C60CFA295-
Αναγνωριστικόhttps://ieeexplore.ieee.org/document/4626087-
Αναγνωριστικόhttps://doi.org/10.1109/TSP.2008.924144-
Γλώσσαen-
Μέγεθος14 pagesen
ΤίτλοςNon-parametric Identification of anisotropic (Elliptic) correlations in spatially distributed data setsen
ΔημιουργόςChorti Arseniael
ΔημιουργόςChristopoulos Dionysiosen
ΔημιουργόςΧριστοπουλος Διονυσιοςel
ΕκδότηςInstitute of Electrical and Electronics Engineersen
ΠερίληψηRandom fields are useful models of spatially variable quantities, such as those occurring in en- vironmental processes and medical imaging. The fluctuations obtained in most natural data sets are typically anisotropic. The parameters of anisotropy are often determined from the data by means of empirical methods or the computationally expensive method of maximum likelihood. In this paper we propose a systematic method for the identification of geometric (elliptic) anisotropy parameters of scalar fields. The proposed method is computationally efficient, non-parametric, non-iterative, and it applies to differentiable random fields with normal or lognormal probability density functions. Our approach uses sample based estimates of the random field spatial derivatives that we relate through closed form expressions to the anisotropy parameters. This paper focuses on two spatial dimensions. We investigate the performance of the method on synthetic samples with Gaussian and Mate ́rn correlations, both on regular and irregular lattices. The systematic anisotropy detection provides an important pre-processing stage of the data. Knowledge of the anisotropy parameters, followed by suitable rotation and rescaling transformations restores isotropy thus allowing classical interpolation and signal processing methods to be applied.en
ΤύποςPeer-Reviewed Journal Publicationen
ΤύποςΔημοσίευση σε Περιοδικό με Κριτέςel
Άδεια Χρήσηςhttp://creativecommons.org/licenses/by/4.0/en
Ημερομηνία2015-09-25-
Ημερομηνία Δημοσίευσης2008-
Θεματική ΚατηγορίαAnisotropic magnetoresistanceen
Θεματική ΚατηγορίαBiomedical imagingen
Θεματική ΚατηγορίαFluctuationsen
Θεματική ΚατηγορίαMaximum likelihood detectionen
Θεματική ΚατηγορίαMaximum likelihood estimationen
Θεματική ΚατηγορίαProbability density functionen
Θεματική ΚατηγορίαLatticesen
Θεματική ΚατηγορίαSignal restorationen
Θεματική ΚατηγορίαInterpolationen
Θεματική ΚατηγορίαSignal processingen
Βιβλιογραφική ΑναφοράA. Chorti and D.T. Hristopulos, "Non-parametric identification of anisotropic (Elliptic) correlations in spatially distributed data sets," IEEE Trans. Signal Process., vol. 56, no. 10, pp 4738-4751, Oct. 2008. doi: 10.1109/TSP.2008.924144en

Υπηρεσίες

Στατιστικά