A novel signal diagnosis technique using pseudo complex-valued autoregressive technique

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摘要

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.

论文关键词:Autoregressive model,Complex-valued data (CVD),Complex-valued neural network (CVNN),Diabetes,Parametric models

论文评审过程:Available online 30 December 2010.

论文官网地址:https://doi.org/10.1016/j.eswa.2010.11.005