碩士 / 中原大學 / 資訊工程研究所 / 89 / Underwater acoustic signal is affected by various factors, and it reveal characteristics of non-linear and time-variant. Therefore, a practical recognition system is proposed which consist of two parts. The One is underwater acoustic signal feature extraction by using wavelet packets and Hilbert Transform. The other is the signal pattern recognition by using Adaptive Network Fuzzy Inference System (ANFIS). Finally, combine the two procedures and establish a practical recognition system.
During the feature parameter extraction stage, signal characteristic analysis and feature selection is discussed. It has been proved that using the wavelet packet decomposition method, and then apply the Hilbert transform can get representative pattern feature parameters of each sample classification individually.
During the Adaptive Network Fuzzy Inference System modeling stage, each ship’s template feature parameters are utilized on to construct the preliminary fuzzy rules and membership functions, and solve the result by using the hybrid learning algorithm. Then, based on the adjustment of fuzzy rules or membership functions, an optimum recognition system is obtained.
| Identifer | oai:union.ndltd.org:TW/089CYCU5392008 |
| Date | January 2001 |
| Creators | I-HSIU Lin, 林怡秀 |
| Contributors | Chu-Kuei Tu, 杜筑奎 |
| Source Sets | National Digital Library of Theses and Dissertations in Taiwan |
| Language | zh-TW |
| Detected Language | English |
| Type | 學位論文 ; thesis |
| Format | 74 |
Page generated in 0.0084 seconds