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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Bibliographic Details
Published in计算机应用研究 Vol. 31; no. 12; pp. 3825 - 3827
Main Author 胡学友 李锐
Format Journal Article
LanguageChinese
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
Subjects
S变换
广义S变换
时频表示
能量聚集度提高
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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ISSN1001-3695
DOI10.3969/j.issn.1001-3695.2014.12.078

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Summary: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.
Bibliography: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.
ISSN:1001-3695
DOI:10.3969/j.issn.1001-3695.2014.12.078