TY - GEN
T1 - Comparison of methods for signal analysis in the time-frequency domain
AU - Alvarez, Robin
AU - Borbor, Erick
AU - Grijalva, Felipe
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/11
Y1 - 2019/11
N2 - This paper shows the most relevant results of the comparison of four signal analysis methods in the time-frequency domain: Short Time Fourier Transform, Wigner-Ville Distribution, Wavelets and Matching Pursuit, using an artificially created signal. This was done in order to look for the advantages and disadvantages of each of these methods in terms of frequency resolution, time resolution, detection and computational load. For the comparison, five experiments were performed with the artificial signal. Each new test demands more strict conditions for time resolution, frequency resolution and component detection due to the amplitude reduces and frequency separation decreases among components. The results show that, the best method in terms of frequency resolution, detection and computational load is the Short Time Fourier Transform. On the other hand, Bump Wavelet, which is also the best among the wavelets analyzed, has the best time resolution allowing to distinguish the start and end times of each component of the signal with excellent precision for each of the tests performed.
AB - This paper shows the most relevant results of the comparison of four signal analysis methods in the time-frequency domain: Short Time Fourier Transform, Wigner-Ville Distribution, Wavelets and Matching Pursuit, using an artificially created signal. This was done in order to look for the advantages and disadvantages of each of these methods in terms of frequency resolution, time resolution, detection and computational load. For the comparison, five experiments were performed with the artificial signal. Each new test demands more strict conditions for time resolution, frequency resolution and component detection due to the amplitude reduces and frequency separation decreases among components. The results show that, the best method in terms of frequency resolution, detection and computational load is the Short Time Fourier Transform. On the other hand, Bump Wavelet, which is also the best among the wavelets analyzed, has the best time resolution allowing to distinguish the start and end times of each component of the signal with excellent precision for each of the tests performed.
KW - Fourier
KW - Matching Pursuit
KW - Time-frequency analysis
KW - Wavelets
KW - Wigner-Ville distribution
UR - https://www.scopus.com/pages/publications/85082025543
U2 - 10.1109/ETCM48019.2019.9014860
DO - 10.1109/ETCM48019.2019.9014860
M3 - Contribución a la conferencia
AN - SCOPUS:85082025543
T3 - 2019 IEEE 4th Ecuador Technical Chapters Meeting, ETCM 2019
BT - 2019 IEEE 4th Ecuador Technical Chapters Meeting, ETCM 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th IEEE Ecuador Technical Chapters Meeting, ETCM 2019
Y2 - 13 November 2019 through 15 November 2019
ER -