## 5 Conclusions  
The article presents the preliminary results of the analysis of the possibility of using the Fourier and the CZT transforms to determine image rastering parameters in the process of electromagnetic infiltration. Particular attention was paid to the accuracy of determining the line length of the reconstructed image based on the accuracy of determining the value of the horizontal sync frequency of the eavesdropped display. The precision of the determination of the line length of the image is of great importance in the case of further processing of the reconstructed image, e.g., in accordance with the coherent summation algorithm to improve the SNR value. The results of the analyses presented in the article clearly show a significant advantage of using the FFT transform in the case when the critical parameter is the calculation time and the very ability to perform the calculations. The greater computational complexity of the CZT transform means that its calculation is at least a dozen times longer (e.g., for a data string with a length of 22, the FFT calculation time is 0.19 s for the Pentium C2Q Q8300 computer and 0.06 s for the Pentium i9-10900X computer, respectively); however, it is still a better approximation of the estimated line length of the reconstructed image. In the case of a data string with a length of 25, the \begin{table}
\begin{tabular}{c c c c c c} \hline \multirow{2}{*}{**Image**} & **Receiving Bandwidth** & **Sampling Rate** & **Real Line** & **Designated Line** & **Estimation** \\  & **Bandwidth** & \(f_{s}\) **[MS/s]** & **Length \(R_{H}\)** & **Length \(R_{H}^{\prime}\)** & **Inaccuracy** \\  & & 62.5 & 925.623100 & 925.623101 & 0.000001 \\ \hline \multirow{8}{*}{Window of MS Word editor} & \multirow{2}{*}{20} & 125.0 & 1851.246230 & 1851.245408 & 0.000822 \\ \cline{3-6}  & & 250.0 & 3702.492190 & 3702.492227 & 0.000037 \\ \cline{3-6}  & & 500.0 & 7404.983240 & 7405.000339 & 0.017099 \\ \hline \multirow{8}{*}{Window of MS Word editor} & \multirow{8}{*}{20} & 62.5 & 925.623270 & 925.623454 & 0.000184 \\ \cline{3-6}  & & 125.0 & 1851.246890 & 1851.246908 & 0.000018 \\ \cline{3-6}  & & 250.0 & 3702.493120 & 3702.482520 & 0.010600 \\ \cline{3-6}  & & 500.0 & 7404.985540 & 7404.916330 & 0.069210 \\ \cline{3-6}  & & 62.5 & 925.623420 & 925.623366 & 0.000054 \\ \cline{3-6}  & & 125.0 & 1851.246740 & 1851.246290 & 0.000450 \\ \cline{3-6}  & & 250.0 & 3702.493160 & 3702.493463 & 0.000303 \\ \cline{3-6}  & & 500.0 & 7404.982540 & 7404.976336 & 0.006204 \\ \hline \end{tabular}
\end{table} 
Table 10: _Cont._calculation times are 1.96 s and 0.43 s, respectively. Using the CZT transform under these conditions requires \(2^{22}\) 15.26 s, 2.74 s and 298.82 s, 26.51 s for a data string of \(2^{25}\) in length, respectively. After a fixed amount of RAM, the use of the FFT transform is possible for data strings of much longer length. The advantage of the CZT transform over the FFT transform consists of increasing the accuracy of calculations related to the narrowing of the frequency range under analysis. In the case of the ordinary FFT transform, its resolution defined by the formula (1) covers the entire range from 0 to \(\frac{f_{s}}{2}\) Hz. However, in the case of the CZT transform, the resolution of the spectrum determination can be increased by performing the analysis only in the given frequency sub-range, with the accuracy defined by number of samples. The use of the CZT transform requires the knowledge of the limits of the analyzed frequency sub-range. Therefore, when determining the rasterization parameters of unknown signals, both transforms can be used together--FFT to roughly define the sought values \(F_{H}\) and \(F_{V}\), and CZT to refine them.