## 3 TF Transforms and Results
### Qualitative Data Analysis Results  
The diagram in Figure 3 shows the complete process of the \(U_{\text{BN}}\) signal TF analysis. Two main stages can be distinguished. The first refers to the computations of six TFRs by applying all considered methods and their configurations for each analyzed MBN signal. During the second stage, the feature extraction procedure was applied, allowing for the definition of several TF parameters for each obtained TF distribution. The procedure of processing the \(U_{\text{BN}}\) signal was the same for all transformations. Figure 4 shows the TF distributions for all five transformations obtained for previously discussed configuration along with the distribution an exemplary TF parameter plotted as a function of magnetizing angle. Figure 4a presents the STFT spectrograms. Based on them, one can notice the increase in MBN activity with the increasing magnetizing angle from \(\alpha\) = 0\({}^{\circ}\) to \(\alpha\) = 90\({}^{\circ}\), and then a decrease in the further angular range up to 180\({}^{\circ}\). Considering the spectrogram achieved for the angle \(\alpha\) = 0\({}^{\circ}\), three local areas of intensive MBN activity can be distinguished. The first area of activity is located around 0.020 s, the second one close to 0.028 s and the third one to 0.035 s. These three main areas of activity can be related to the phenomena occurring during the reorganization of the magnetic domain structure in the following order: domain nucleation, 180\({}^{\circ}\) domain wall movement and 90\({}^{\circ}\) domain wall movement [20; 34]. Next, these areas successively merge when the magnetizing angle \(\alpha\) increases, what leads to the formation of two dominant activity intervals. The following stages of the process can be observed for \(\alpha\) range until 90\({}^{\circ}\). Then, for an angle greater than 90\({}^{\circ}\), the two areas gradually divide into three again. In Figure 4b, the CWT scalograms are  
Figure 3: Calculation procedure. presented. To allow the comparison, the frequency axis is presented in a linear scale. One can see that the MBN activity increases with the increasing value of the angle \(\alpha\) up to 90\({}^{\circ}\), and then it decreases--similarly to the STFT distributions. However, in the CWT case, the three areas of activity are not as clearly visible as they are for the spectrograms. For the angle \(\alpha=90^{\circ}\), it is possible to identify the two areas of activity but not as precisely as in the case of the spectrogram obtained for the STFT transformation. Figure 4: Spectrograms obtained on the basis of considered transformations: (**a**) STFT (**b**) CWT (**c**) FSST (**d**) WSST (**e**) SPWVDv1 (**f**) SPWVDv2. Further, Figure 4c presents spectrograms of the FSST transformation. It does not allow one to observe areas of activity as clearly as in the case of the STFT. However, two main areas of activity can be noticed in the distribution for the angle \(\alpha=90^{\circ}\). The MBN activity rises and falls are the same as in the cases of the previously discussed transformations. The results of the WSST scalograms are shown in Figure 4d. From the obtained results, none of qualitative analysis of MBN activity can be performed. The obtained distributions contain information that is unreadable for a human and require the use of methods which would allow one to extract the hidden information. Finally, Figure 4e,f present the absolute value of the SPWVD distributions achieved for two utilized configurations. In the first version (SPWVDv1--transformation parameters corresponding to the STFT ones), similarly as in previous cases, the MBN activity increases with the increasing angle up to \(\alpha=90^{\circ}\), and then decreases. However, in this transformation setup (limited resolution), none of the activity intervals can be distinguished. A visible increase in the discrimination of MBN activity areas was obtained in the second case (Figure 4f--SPWVDv2).