Investigation of complexity of extraction accuracy modeling cardio signals in two ways

How to extract information intensively from cardio signals for the diagnosis of diseases and assessment of heart function is a topical subject. Heart is not a periodic oscillator under normal physiologic conditions and standard linear measures may not be able to detect subtle, but important changes in heart time series, whereas, most of nonlinear measures suffer from the curse of dimensionally. In this paper, we show the results of cardio signals identification using the proposed structure based on H rank function employment.