Evaluation of background noise for significance level identification

The paper deals with the identification of the significance level for testing the time-frequency transform of the data. The usual procedure of time-frequency significance testing is based on the knowledge of background spectrum. Very often, we have certain expectations about the character the background noise (White noise, Red noise, etc.). Our paper deals with the case when the character of the noise is unknown and may not be Gaussian despite our assumptions. Thus, we propose how to identify our own critical values for testing time-frequency transform significance with respect to the data character. We compare our findings with the critical quantile of χ
²
₂
.