时频聚集性能优化的广义S变换
TP391%TN911.23; S变换是一种具有短时傅里叶变换和小波变换优点的时频分析方法,已有的一些基于能量聚集度量的优化方法集中度不高,影响了信号检测等应用中时频域局部定位的精度.为了提高S变换的时频聚集性能,提出了一种新的时频能量聚集度量方法优化广义S变换,提高了算法的时频集中度和短时傅里叶变换、S变换、广义S变换等方法实验比较,表明提出的方法能有效地提高广义S变换的能量集中度,并具有较强的抗噪声性能....
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| Published in | 计算机应用研究 Vol. 31; no. 12; pp. 3825 - 3827 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
合肥学院电子信息与电气工程系,合肥,230601%安徽大学计算智能与信号处理教育部重点实验室,合肥,230039
2014
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1001-3695 |
| DOI | 10.3969/j.issn.1001-3695.2014.12.078 |
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| Abstract | TP391%TN911.23; S变换是一种具有短时傅里叶变换和小波变换优点的时频分析方法,已有的一些基于能量聚集度量的优化方法集中度不高,影响了信号检测等应用中时频域局部定位的精度.为了提高S变换的时频聚集性能,提出了一种新的时频能量聚集度量方法优化广义S变换,提高了算法的时频集中度和短时傅里叶变换、S变换、广义S变换等方法实验比较,表明提出的方法能有效地提高广义S变换的能量集中度,并具有较强的抗噪声性能. |
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| AbstractList | TP391%TN911.23; S变换是一种具有短时傅里叶变换和小波变换优点的时频分析方法,已有的一些基于能量聚集度量的优化方法集中度不高,影响了信号检测等应用中时频域局部定位的精度.为了提高S变换的时频聚集性能,提出了一种新的时频能量聚集度量方法优化广义S变换,提高了算法的时频集中度和短时傅里叶变换、S变换、广义S变换等方法实验比较,表明提出的方法能有效地提高广义S变换的能量集中度,并具有较强的抗噪声性能. S变换是一种具有短时傅里叶变换和小波变换优点的时频分析方法,已有的一些基于能量聚集度量的优化方法集中度不高,影响了信号检测等应用中时频域局部定位的精度。为了提高S变换的时频聚集性能,提出了一种新的时频能量聚集度量方法优化广义S变换,提高了算法的时频集中度和短时傅里叶变换、S变换、广义S变换等方法实验比较,表明提出的方法能有效地提高广义S变换的能量集中度,并具有较强的抗噪声性能。 |
| Author | 胡学友 李锐 |
| AuthorAffiliation | 合肥学院电子信息与电气工程系,合肥230601 安徽大学计算智能与信号处理教育部重点实验室,合肥230039 |
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| Author_FL | HU Xue-you LI Rui |
| Author_FL_xml | – sequence: 1 fullname: HU Xue-you – sequence: 2 fullname: LI Rui |
| Author_xml | – sequence: 1 fullname: 胡学友 李锐 |
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| ClassificationCodes | TP391%TN911.23 |
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| Copyright | Copyright © Wanfang Data Co. Ltd. All Rights Reserved. |
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| DocumentTitleAlternate | Time-frequency concentration optimization for generalized S-transform |
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| Keywords | 广义S变换 能量聚集度提高 generalized S-transform S变换 时频表示 time-frequency representation concentration enhancement S-transform |
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| Notes | 51-1196/TP HU Xue-you,LI Rui（1. Dept. of Electronics ＆ Electrical Engineering, Hefei University, Hefei 230601, China ; 2. Key Laboratory of Intelligence Computing ＆ Signal Processing of Ministry of Education, Anhui University, Hefei 230039, China） time-frequency representation;S-transform;generalized S-transform;concentration enhancement The S-transform（ ST） was one of the useful time-frequency analysis method combined the short time Fourier（ STFT） and wavelet transforms. Several optimal methods based on concentration measure had been proposed by some researchers with poor energy concentration for some signals time-frequency localization in signal detection. This paper proposed a modified generalized S-transform（ GST） to enhance the energy concentration in the time-frequency domain using a new concentration measure. Experimental results show the proposed method has achieved higher signal concentration and has good anti-noise ability compared to previous optimal methods,such as STFT,ST and GST. |
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| PublicationTitle | 计算机应用研究 |
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| PublicationYear | 2014 |
| Publisher | 合肥学院电子信息与电气工程系,合肥,230601%安徽大学计算智能与信号处理教育部重点实验室,合肥,230039 |
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| SubjectTerms | S变换 广义S变换 时频表示 能量聚集度提高 |
| Title | 时频聚集性能优化的广义S变换 |
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