Wavelet denoising and feature extraction of seismic signal for footstep detection
文献类型：会议论文
| 作者 | Xing, HF ; Li, F ; Liu, YL |
| 出版日期 | 2007 |
| 会议名称 | 5th international conference on wavelet analysis and pattern recognition |
| 会议日期 | nov 02-04, 2007 |
| 会议地点 | beijing, peoples r china |
| 关键词 | wavelet denoising seismic signal footstep detection feature extraction |
| 页码 | vols 1-4,proceedings: 218-223 |
| 通讯作者 | xing, hf, chinese acad sci, inst semicond, state key lab integrated optoelect, beijing 100083, peoples r china. |
| 中文摘要 | seismic sensors are widely used to detect moving target in ground sensor networks. footstep detection is very important for security surveillance and other applications. because of non-stationary characteristic of seismic signal and complex environment conditions, footstep detection is a very challenging problem. a novel wavelet denoising method based on singular value decomposition is used to solve these problems. the signal-to-noise ratio (snr) of raw footstep signal is greatly improved using this strategy. the feature extraction method is also discussed after denosing procedure. comparing, with kurtosis statistic feature, the wavelet energy feature is more promising for seismic footstep detection, especially in a long distance surveillance. |
| 英文摘要 | seismic sensors are widely used to detect moving target in ground sensor networks. footstep detection is very important for security surveillance and other applications. because of non-stationary characteristic of seismic signal and complex environment conditions, footstep detection is a very challenging problem. a novel wavelet denoising method based on singular value decomposition is used to solve these problems. the signal-to-noise ratio (snr) of raw footstep signal is greatly improved using this strategy. the feature extraction method is also discussed after denosing procedure. comparing, with kurtosis statistic feature, the wavelet energy feature is more promising for seismic footstep detection, especially in a long distance surveillance.; zhangdi于2010-03-09批量导入; made available in dspace on 2010-03-09t02:11:57z (gmt). no. of bitstreams: 1 704.pdf: 299654 bytes, checksum: f528f9199bcbc8dac0d8f76308cfc5d5 (md5) previous issue date: 2007; machine learning & cybernet res inst.; ieee smc soc.; chinese assoc artificial intelligence.; univ sci & technol beijing.; tsinghua univ.; peking univ.; chongqing univ.; hebei univ.; hong kong baptist univ.; natl nat sci fdn china.; [xing, huai-fei; li, fang; liu, yu-liang] chinese acad sci, inst semicond, state key lab integrated optoelect, beijing 100083, peoples r china |
| 收录类别 | CPCI-S |
| 会议主办者 | machine learning & cybernet res inst.; ieee smc soc.; chinese assoc artificial intelligence.; univ sci & technol beijing.; tsinghua univ.; peking univ.; chongqing univ.; hebei univ.; hong kong baptist univ.; natl nat sci fdn china. |
| 会议录 | 2007 international conference on wavelet analysis and pattern recognition
 |
| 会议录出版者 | ieee ; 345 e 47th st, new york, ny 10017 usa |
| 学科主题 | 光电子学 |
| 会议录出版地 | 345 e 47th st, new york, ny 10017 usa |
| 语种 | 英语 |
| ISBN号 | 978-1-4244-1065-1 |
| 源URL | [http://ir.semi.ac.cn/handle/172111/7848]  |
| 专题 | 半导体研究所_中国科学院半导体研究所（2009年前） |
| 推荐引用方式 GB/T 7714 | Xing, HF,Li, F,Liu, YL. Wavelet denoising and feature extraction of seismic signal for footstep detection[C]. 见:5th international conference on wavelet analysis and pattern recognition. beijing, peoples r china. nov 02-04, 2007. |
入库方式： OAI收割
来源：半导体研究所
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