Table 1.

Some features and their formulas used to feed classifier

Feature description	Formula	Feature description	Formula
Mean value	$\frac{{\displaystyle {\sum }_{i=1}^n{x}_i}}{n}$	Third central moment	$\frac{{\displaystyle {\sum }_{i=1}^n{\left(x_i-\overline{x}\right)}^3}}{n}$
Standard deviation	$\sqrt{\frac{1}{n}{\displaystyle {\sum }_{i=1}^n{\left(x_i-\overline{x}\right)}^2}}$	Forth central moment	$\frac{{\displaystyle {\sum }_{i=1}^n{\left(x_i-\overline{x}\right)}^4}}{n}$
Root mean square	$\sqrt{\frac{{\displaystyle {\sum }_{i=1}^n{\left(x_i\right)}^2}}{n}}$	Kurtosis	$\frac{\frac{1}{n}{\displaystyle {\sum }_{i=1}^n{\left(x_i-\overline{x}\right)}^4}}{{\left(\frac{1}{n}{\displaystyle {\sum }_{i=1}^n{\left(x_i-\overline{x}\right)}^2}\right)}^2}$
Skewness	$\frac{\frac{1}{n}{\displaystyle {\sum }_{i=1}^n{\left(x_i-\overline{x}\right)}^3}}{{\left(\frac{1}{n}{\displaystyle {\sum }_{i=1}^n{\left(x_i-\overline{x}\right)}^2}\right)}^{3/2}}$	Peak value	max |x i|