TY - JOUR
T1 - On instantaneous frequency
AU - Huang, Norden E.
AU - Wu, Zhaohua
AU - Long, Steven R.
AU - Arnold, Kenneth C.
AU - Chen, Xianyao
AU - Blank, Karin
N1 - Funding Information:
This study is instigated by the suggestions of Dr. James F. Kaiser of Duke University, whose insistence on detailed comparisons between Teager energy operator method with all the others motivated us to examine the Hilbert transform in great details. Through the comparisons, we found the shortcomings of HT and proposed the present improvements through normalization and direct quadrature. We would like to express our most sincere thanks to J.F.K. The authors are benefited from constructive suggestions from the referees of an earlier version of this manuscript, and we would like to extend our deepest appreciations to them. This research was initiated many years ago. During the course, our research was supported in part by a grant from Office of Naval Research, N0001403IP20094, a grant from Federal Highway Administration, DTFH61-08-00028, and a grant from NSC95-2119-M-008-031-MY3, and finally a grant from NCU 965941 that have made the conclusion of this study possible. NEH is supported by a TSMC endowed chair at NCU. ZW is supported by National Science Foundation of USA under grant ATM-0653136 and ATM-0917743. A patent has been filed by NASA on the empirical AM–FM decomposition through spline fitted normalization scheme in computing the IF.
PY - 2009/4
Y1 - 2009/4
N2 - Instantaneous frequency (IF) is necessary for understanding the detailed mechanisms for nonlinear and nonstationary processes. Historically, IF was computed from analytic signal (AS) through the Hilbert transform. This paper offers an overview of the difficulties involved in using AS, and two new methods to overcome the difficulties for computing IF. The first approach is to compute the quadrature (defined here as a simple 90° shift of phase angle) directly. The second approach is designated as the normalized Hilbert transform (NHT), which consists of applying the Hilbert transform to the empirically determined FM signals. Additionally, we have also introduced alternative methods to compute local frequency, the generalized zero-crossing (GZC), and the teager energy operator (TEO) methods. Through careful comparisons, we found that the NHT and direct quadrature gave the best overall performance. While the TEO method is the most localized, it is limited to data from linear processes, the GZC method is the most robust and accurate although limited to the mean frequency over a quarter wavelength of temporal resolution. With these results, we believe most of the problems associated with the IF determination are resolved, and a true timefrequency analysis is thus taking another step toward maturity.
AB - Instantaneous frequency (IF) is necessary for understanding the detailed mechanisms for nonlinear and nonstationary processes. Historically, IF was computed from analytic signal (AS) through the Hilbert transform. This paper offers an overview of the difficulties involved in using AS, and two new methods to overcome the difficulties for computing IF. The first approach is to compute the quadrature (defined here as a simple 90° shift of phase angle) directly. The second approach is designated as the normalized Hilbert transform (NHT), which consists of applying the Hilbert transform to the empirically determined FM signals. Additionally, we have also introduced alternative methods to compute local frequency, the generalized zero-crossing (GZC), and the teager energy operator (TEO) methods. Through careful comparisons, we found that the NHT and direct quadrature gave the best overall performance. While the TEO method is the most localized, it is limited to data from linear processes, the GZC method is the most robust and accurate although limited to the mean frequency over a quarter wavelength of temporal resolution. With these results, we believe most of the problems associated with the IF determination are resolved, and a true timefrequency analysis is thus taking another step toward maturity.
KW - Hilbert transform
KW - Instantaneous frequency
KW - empirical AM/FM decomposition
KW - empirical mode decomposition
KW - normalized intrinsic mode function
KW - quadrature
UR - http://www.scopus.com/inward/record.url?scp=77951668826&partnerID=8YFLogxK
U2 - 10.1142/S1793536909000096
DO - 10.1142/S1793536909000096
M3 - Review article
AN - SCOPUS:77951668826
SN - 1793-5369
VL - 1
SP - 177
EP - 229
JO - Advances in Adaptive Data Analysis
JF - Advances in Adaptive Data Analysis
IS - 2
ER -