Signal Detection in Underwater Sound Using the Empirical Mode Decomposition
| Autor: | Jenny Chih-Yu Lee, Fu-Tai Wang, Shun-Hsyung Chang |
|---|---|
| Rok vydání: | 2006 |
| Předmět: |
Discrete wavelet transform
Signal processing Basis (linear algebra) Computer science Applied Mathematics Speech recognition Detector Mode (statistics) Computer Graphics and Computer-Aided Design Hilbert–Huang transform Wavelet Signal Processing Detection theory Electrical and Electronic Engineering Algorithm |
| Zdroj: | IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences. :2415-2421 |
| ISSN: | 1745-1337 0916-8508 |
| DOI: | 10.1093/ietfec/e89-a.9.2415 |
| Popis: | In this article, the empirical mode decomposition (EMD) is introduced to the problem of signal detection in underwater sound. EMD is a new method pioneered by Huang et al. for non-linear and non-stationary signal analysis. Based on the EMD, any input data can be decomposed into a small number of intrinsic mode functions (IMFs) which can serve as the basis of non-stationary data for they are complete, almost orthogonal, local and adaptive. Another useful tool for processing transient signals is discrete wavelet transform (DWT). In this paper, these IMFs are applied to determine when the particular signals appear. From the computer simulation, based on the receiver operating characteristics (ROC), a performance comparison shows that this proposed EMD-based detector is better than the DWT-based method. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|