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The nonlinear and dynamic accommodating capability of time domain models makes them a useful representation of chaotic time series for analysis, modeling and prediction. This paper is devoted to the modeling and prediction of chaotic time series with hidden attractors using a nonlinear autoregressive model with exogenous inputs (NARX) based on a novel recurrent fuzzy functions (RFFs) approach. Case...
Investigating novel efficient feature extraction approach applied to the lung sound signal is a necessary method to improve the performance of respiratory abnormality recognition. Owing to the fact that the Recurrence Quantification Analysis (RQA) is a proper approach for insight into dynamic system, this paper proposed a new method for feature extraction from the lung sound signals. The method is...
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