Please use this identifier to cite or link to this item: http://repository.elizadeuniversity.edu.ng/jspui/handle/20.500.12398/596
Title: A novel signal diagnosis technique using pseudo complex-valued autoregressive technique
Authors: Aibinu, Abiodun M.
Salami, Momoh-Jimoh E.
Shafie, Amir A.
Keywords: Autoregressive model
Complex-valued data (CVD)
Complex-valued neural network (CVNN)
Diabetes
Parametric models
Issue Date: 1-Aug-2011
Publisher: Pergamon
Citation: Aibinu, A. M., Salami, M. J. E., & Shafie, A. A. (2011). A novel signal diagnosis technique using pseudo complex-valued autoregressive technique. Expert Systems with Applications, 38(8), 9063-9069.
Abstract: In this paper, a new method of biomedical signal classification using complex- valued pseudo autoregressive (CAR) modeling approach has been proposed. The CAR coefficients were computed from the synaptic weights and coefficients of a split weight and activation function of a feedforward multilayer complex valued neural network. The performance of the proposed technique has been evaluated using PIMA Indian diabetes dataset with different complex-valued data normalization techniques and four different values of learning rate. An accuracy value of 81.28% has been obtained using this proposed technique.
URI: https://doi.org/10.1016/j.eswa.2010.11.005
http://repository.elizadeuniversity.edu.ng/jspui/handle/20.500.12398/596
Appears in Collections:Research Articles

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