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

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.

Research highlights
► New method of data classification using pseudo modeling approach.
► Computation of the required model coefficients for the proposed pseudo modeling approach involve the use of complex valued neural network technique for efficient and effective data classification.
► Accuracy value of 81.28% has been obtained in this work using the proposed pseudo modeling approach.