THE ENTROPY OF DISCRETE-TIME FRACTIONAL GAUSSIAN NOISE AND ITS APPLICATION TO THE ELECTROMYOGRAM OF EXTERNAL URETHRAL SPHINCTER SIGNALS

In this work, we will study the Hurst parameter embedded in the discrete-time fraction Gaussian noise (DFGN) and derive the entropy with this parameter. It will be applied to the electromyogram (EMG) of external urethral sphincter (EUS). These signals come from intact rats and the injured ones from spinal cord injury (SCI). Analysis indicates that we can discriminate between intact and SCI rats from this information.