Ripple Signal Analysis in the GIBBS Phenomenon
Analisa Sinyal Ripple pada Fenomena GIBBS
DOI:
https://doi.org/10.30649/je.v6i1.144Keywords:
Time Signal, Spectrum, Frequency Domain, Sine Wave, GraphAbstract
The frequency domain is a method of analyzing signals based on their frequencies rather than time. A time-domain graph shows how a signal changes over time, while the frequency domain shows the frequency content and amplitude of each component. The Fourier Transform is used to convert a signal from the time domain to the frequency domain, while the inverse transform converts it back. The frequency spectrum displays the amplitude and phase of each frequency component of the signal. This analysis is important in fields such as physics, electronics, control systems, and statistics. Some techniques also combine the time and frequency domains to analyze signals that vary over time.
References
D. Andreas, Muhammad Dodi Utomo, Vicko Ghulam Fathurrohman, and Dedi Risaldi, “Perancangan simulasi Lampu Otomatis Dengan sensor TMP36, Ldr Dan Ultrasonik menggunakan TINKERCAD,” J-Eltrik, vol. 3, no. 1, pp. 2, 2022. doi:10.30649/je.v3i1.59
S. A. Broughton and K. Bryan, "The discrete Fourier transform," in Discrete Fourier Analysis and Wavelets, New York, Wiley-Interscience, 2008, p. 72.
M. I. H., D. N. Sugianto and P. Purwanto, "Analisis Transformasi Dan Spektrum Gelombang Berarah Di Perairan Sayung Demak Jawa Tengah," JURNAL OSEANOGRAFI, vol. 6, no. 1, p. 1, 2017.
M. anike, "Analisa Pengolahan Citra Menggunakan Metode Transformasi Fourier," in Konferensi Nasional Sistem dan Informatika, Bali, 2015.
S. R. K. Daniel S Pamungkas and B. F. Simamora, "Perbandingan Antara Domain Waktu dan," Jurnal Rekayasa Elektrika, vol. 17, no. 1, p. 38, 2021.
Supriyadi, "COMMUNITY OF PRACTITIONERS : SOLUSI ALTERNATIF BERBAGI," Lentera Pustaka, vol. 2, no. 2, p. 85, 2016.
Santoso, T. B., Haniah, M., & Nur, A. (2012). Praktikum Sinyal dan Sistem. Surabaya: Politeknik Elektronika Negeri Surabaya.
Gengsheng L. Zeng and Richard J. Allred, “Partitioned image filtering for reduction of the Gibbs phenomenon,” J. Nucl. Med. Technol., vol. 37, no. 2, pp. 96-100, May 2009.
C. Karanikas and N. Atreas, “Gibbs’ phenomenon for sampling series and what to do about it,” Journal of Fourier Analysis and Applications, vol. 4, no. 3, pp. 357-375, May 1998.
N. Atreas and C. Karanikas, “Gibbs phenomenon on sampling series based on Shannon’s and Meyer’s wavelet analysis,” Journal of Fourier Analysis and Applications, vol. 5, pp. 575-588, Nov. 1999.
S. S. K. Tadikonda and H. Baruh, “Gibbs phenomenon in structural mechanics,” AIAA Journal, published online 17 May 2012.
Anne Gelb and Jared Tanner, “Robust reprojection methods for the resolution of the Gibbs phenomenon,” Applied and Computational Harmonic Analysis, vol. 20, no. 1, pp. 3-25, Jan. 2006.
Milica Stojanović, Milan Simić, Jelena Đorđevic Kozarov, and Dragan Živanović, “Reduction of Gibbs Phenomenon in EOG Signal Measurement Using the Modified Digital Stochastic Measurement Method,” Facta Universitatis, Series: Automatic Control and Robotics, vol. 22, no. 2, pp. 087-101, 2023.
P. M. Tagade and H.-L. Choi, “Mitigating Gibbs Phenomena in Uncertainty Quantification With a Stochastic Spectral Method,” Journal of Verification, Validation and Uncertainty Quantification, vol. 2, no. 1, Art. no. 011003, Mar. 2017.
S.-C. Lin, S.-H. Xu, Y.-H. Chen, C.-W. Chang, and Y.-Jan Emery Chen, “Gibbs-Phenomenon-Reduced Digital PWM for Power Amplifiers Using Pulse Modulation,” IEEE Access, vol. 7, pp. 178788-178797, 2019.
