Hermite–Gauss wavelets: synthesis of discrete forms and investigation of properties
https://doi.org/10.17586/2226-1494-2025-25-4-789-796
Abstract
Considered new results of studies of eigenvectors and vector functions of discrete and continuous Fourier transforms. It is known that such eigenvectors are products of the Gauss function on Hermite polynomials, a name is proposed for the functions obtained on the basis of this product: Hermite-Gauss wavelets. In the paper studies on the base of mathematical analysis methods of continuous functions and numerical methods, the properties and methods of synthesis of eigenvectors and vector functions of discrete and continuous Fourier transforms are investigated. Expressions for calculating the scale parameter and the normalizing factor for discrete forms of Hermite-Gauss wavelets are obtained. The studies performed to prompt that the scale parameter of the discrete form of Hermite-Gauss wavelets depends on the number of samples, and the norm depends on the number of samples and the number of the wavelet. The form of the Fourier transform matrices is obtained which has good conditionality when calculating eigenvectors in the form of Hermite-Gauss wavelets. Hermite-Gauss wavelets form a basis, and therefore can be used in tasks of signal decomposition and synthesis. For choosing a mother wavelet for decomposition and synthesis, firstly one should be guided by the features and properties of the shapes formed by it. For some signals, Morlaix or Daubechy wavelets can give compact decomposition, for others, Hare wavelets, and there are also signals for which Hermite-Gauss wavelets are most effective for spectral decomposition.
About the Authors
A. Yu. GrishentsevRussian Federation
Alexey Yu. Grishentsev, D.Sc., Associate Professor, Associate Professor at the Department
197101; Saint Petersburg
sc 56321138400
N. V. Korovkin
Russian Federation
Nikolay V. Korovkin, D.Sc., Full Professor
195251; Saint Petersburg
sc 6601971248
D. P. Ostrovskii
Russian Federation
Danil P. Ostrovskii, PhD Student
197101; Saint Petersburg
References
1. Korovkin N.V., Gritsutenko S.S. About applicability of the fast fourier transform for a harmonic analisys of non sinusoidal currents and voltages. Proceedings of the Russian Academy of Sciences. Power Engineering, 2017, no. 2, pp. 73–86. (in Russian)
2. Berber S. Theory of the design, and operation of digital filters. Discrete Communication Systems, 2021, pp. 797–823. doi: 10.1093/oso/9780198860792.003.0016
3. Welstead S. Fractal and Wavelet Image Compression Techniques. SPIE Publication, 1999, 254 p.
4. Rioul O., Vetterli M. Wavelets and signal processing. IEEE Signal Processing Magazine, 1991, vol. 8, no. 4, pp. 14–38. doi: 10.1109/79.91217
5. Chen C., Liu M.-Y., Tuzel O., Xiao J. R-CNN for small object detection. Lecture Notes in Computer Science, 2017, vol. 10115, pp. 214–230. doi: 10.1007/978-3-319-54193-8_14
6. Dvornikov S.V., Saukov A.M. Signal identification method based on wavelet-packets. Nauchnoe Priborostroenie, 2004, vol. 14, no. 1, pp. 85–93. (in Russian)
7. Podkur P.N., Smolentsev N.K. Wavelet packet decomposition EEG on the basic frequency rhythms. Tomsk State University Journal of Control and Computer Science, 2016, no. 2 (35), pp. 54–61. (in Russian). doi: 10.17223/19988605/35/6
8. Korobeinikov A.G., Sidorkina I.G. Primary processing of seismic event data using wavelets in MATLAB. Cybernetics and Programming, 2018, no. 1, pp. 36–47. (in Russian). doi: 10.25136/2306-4196.2018.1.25245
9. Kislinski V.S., Grakhova E.P., Abdrakhmanova G.I. Application of wavelets and Hermiteans for simulation of ultra-wideband pulses satisfying to requirements of State Committee of Radio Frequencies. Infokommunikacionnye Tehnologii, 2015, vol. 13, no. 4, pp. 391–398. (in Russian). doi: 10.18469/ikt.2015.13.4.05
10. Lindsey A.R. Wavelet packet modulation for orthogonally multiplexed communication. IEEE Transactions on Signal Processing, 1997, vol. 45, pp. 1336–1339. doi: %10.1109/78.575704
11. Grishentsev A.Yu., Korobeinikov A.G. Application of several wavelets for generating wideband signals. Journal of Instrument Engineering, 2017, vol. 60, no. 8, pp. 712–720. (in Russian). doi: 10.17586/0021-3454-2017-60-8-712-720
12. Grishentsev A.Yu., Korovkin N.V., Korobeynikov A.G. Investigation of the properties of the Fourier transform of Hermite-Gauss wavelets and application of the results obtained in radio electronics problems. Journal of Radio Electronics, 2025, no. 6, pp. 13. (in Russian). doi: 10.30898/1684-1719.2025.6.11
13. Grishentsev A.Yu., Arustamov S.A., Korobeynikov A.G., Kozin O.V. Orthogonal noise-like signal symbols for broadband channel protection. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2019, vol. 19, no. 2, pp. 280–291. (in Russian). doi: 10.17586/2226-1494-2019-19-2-280-291
14. Novikov I.Ya., Stechkin S.B. Basic wavelet theory. Russian Mathematical Surveys, 1998, vol. 53, no. 6, pp. 1159–1231. doi: 10.1070/rm1998v053n06ABEH000089
15. Dremin I.M., Ivanov O.V., Nechitaǐlo V.A. Wavelets and their uses. Physics Uspekhi, 2001, vol. 44, no. 5, pp. 447–478. doi: 10.1070/PU2001v044n05ABEH000918
16. Semenov V.I., Chumarov S.G. From the construction of wavelets based on derivatives of the Gaussian function to the synthesis of filters with a finite impulse response. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2024, vol. 24, no. 2, pp. 306–313. (in Russian). doi: 10.17586/2226-1494-2024-24-2-306-313
17. Landau L.D., Lifshitz E.M. Quantum Mechanics. Non-Relativistic Theory. Moscow, Fizmatgiz Publ., 1963, 704 p. (in Russian)
18. Tokita S., Sugiyama T., Noguchi F., Fujii H., Kobayashi H. An attempt to construct an isosurface having symmetry elements. Journal of Computer Chemistry, Japan, 2005, vol. 5, no. 3, pp. 159–164. doi: 10.2477/jccj.5.159
19. Autocorrelation and fractal properties of the matrix linear unitary Fourier transforms. Radioengineering, 2019, no. 1, pp. 5–14. (in Russian). doi: 10.18127/j00338486-201901-01
20. Molchanov I.N. Machine Methods for Applied Problems Solving. Algebra, Approximation of Functions. Kiev, Naukova dumka, 1987, 287 p. (in Russian)
21. Wilkinson J.H. The Algebraic Eigenvalue Problem. Oxford, Clarendon Press, 1965, 662 p.
Review
For citations:
Grishentsev A.Yu., Korovkin N.V., Ostrovskii D.P. Hermite–Gauss wavelets: synthesis of discrete forms and investigation of properties. Scientific and Technical Journal of Information Technologies, Mechanics and Optics. 2025;25(4):789-796. (In Russ.) https://doi.org/10.17586/2226-1494-2025-25-4-789-796