Determination of complex-valued parametric model coefficients using artificial neural network technique

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dc.contributor.authorAibinu, Abiodun M.
dc.contributor.authorSalami, Momoh-Jimoh E.
dc.contributor.authorShafie, Amir A.
dc.date.accessioned2019-08-14T10:52:15Z
dc.date.available2019-08-14T10:52:15Z
dc.date.issued2010
dc.description.abstractA new approach for determining the coefficients of a complex-valued autoregressive (CAR) and complex-valued autoregressive moving average (CARMA) model coefficients using complex-valued neural network (CVNN) technique is discussed in this paper. The CAR and complex-valued moving average (CMA) coefficients which constitute a CARMA model are computed simultaneously from the adaptive weights and coefficients of the linear activation functions in a two-layered CVNN. The performance of the proposed technique has been evaluated using simulated complex-valued data (CVD) with three different types of activation functions. The results show that the proposed method can accurately determine the model coefficients provided that the network is properly trained. Furthermore, application of the developed CVNN-based technique for MRI K-space reconstruction results in images with improve resolution.en_US
dc.identifier.citationAibinu, A. M., Salami, M. J. E., & Shafie, A. A. (2010). Determination of complex-valued parametric model coefficients using artificial neural network technique. Advances in artificial neural systems, 2010.en_US
dc.identifier.uri10.1155/2010/984381
dc.identifier.urihttp://repository.elizadeuniversity.edu.ng/handle/20.500.12398/462
dc.language.isoenen_US
dc.publisherHindawien_US
dc.subjectcomplex-valued parametricen_US
dc.subjectmodel coefficientsen_US
dc.subjectArtificial neural networken_US
dc.titleDetermination of complex-valued parametric model coefficients using artificial neural network techniqueen_US
dc.typeArticleen_US
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