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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Hajj-Ahmad, A. Garg, R. Min Wu |
| Copyright Year | 1994 |
| Abstract | The Electric Network Frequency (ENF) is the supply frequency of power distribution networks, and is often captured by audio or video measurements recorded near power supplies. The time varying nature of the ENF allows it to be used for such forensic applications as estimating the time and location of media recordings, and discerning their integrity. An initial step in such applications is to extract the ENF signal-instantaneous ENF values over time-as accurately as possible. Existing techniques rely on estimating the ENF around the nominal frequency of 50/60 Hz, or around one of its harmonics at a time. In this letter, a novel spectrum combining approach is proposed, which exploits the presence of the ENF around different harmonics of the nominal frequency. The ENF signal is estimated by combining the ENF at multiple harmonics, based on the local signal-to-noise ratio at each harmonic. A hypothesis testing performance of an ENF-based timestamp verification application is examined to validate that the proposed approach achieves a more robust and accurate performance than conventional ENF estimation techniques. |
| Sponsorship | IEEE Signal Processing Society |
| Starting Page | 885 |
| Ending Page | 888 |
| Page Count | 4 |
| File Size | 769400 |
| File Format | |
| ISSN | 10709908 |
| Volume Number | 20 |
| Issue Number | 9 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-01-01 |
| Publisher Place | U.S.A. |
| Access Restriction | One Nation One Subscription (ONOS) |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Harmonic analysis Frequency estimation Equations Signal to noise ratio Estimation Power system harmonics spectrum combining Electric Network Frequency timestamp verification |
| Content Type | Text |
| Resource Type | Article |
| Subject | Applied Mathematics Signal Processing Electrical and Electronic Engineering |
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