DETECTION OF NON RANDOM PHASE SIGNAL IN ADDITIVE NOISE WITH SURROGATE ANALYSIS

The Surrogate Analysis (SA) is known to detect nonlinear signals, non-stationary signals and ARMA systems driven by non-Gaussian processes. This paper adds to address the detection of non-random phase signal, of which the linear phase signal is the best-known example. This is a new interpretation of the SA. In order to highlights the benefits of the interpretation, a new theoretical signals is constructed. The signal has a perfect Gaussian distribution and is not affected by periodic extension and is a linear phase signal. The SA will be shown able to detect this signal in a noise with exactly the same power spectrum. It will be clear that the SA is able to detect phase linearity even when the data is normally distributed. An application of the detection by SA is given regarding very noisy and short time electrocardiogram (ECG) signal and compared to higher order statistics and normality tests for this purpose.