An Adaptive SVD Method for Solving the Pass-Region Problem in S-Transform Time-Frequency Filters
An Adaptive SVD Method for Solving the Pass-Region Problem in S-Transform Time-Frequency Filters作者机构：School of Electrical and Automation Engineering Hefei University of Technology
出 版 物：《Chinese Journal of Electronics》 (电子学报(英文))
年 卷 期：2015年第24卷第1期
页 面：115-123页
核心收录：
学科分类：0808[工学-电气工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 080902[工学-电路与系统] 08[工学] 0701[理学-数学]
基 金：supported by the National Natural Science Foundation for Distinguished Young Scholars of China(No.50925727) the Young Scientists Fund of the National Natural Science Foundation of China(No.51107034,No.61102035) the National Defense Advanced Research Project(No.C1120110004,No.9140A27020211DZ5102) Foundation for Key Program of Ministry of Education,China(No.313018) the Natural Science Foundation of Hunan Province,China(No.12JJA004,No.2011J4,No.2011JK2023) the Research Foundation of Education Bureau of Hunan Province,China(No.11C0479)
主 题：S-transform Matrix inverse S-transform Time frequency filter Singular value decomposition.
摘 要：S-transform(ST) is an excellent tool for time-frequency filter. There are two factors that influence filtering performance: Inverse s-transform(IST) algorithms and the pass-regions in time-frequency domain. A novel matrix IST algorithm is derived and an adaptive Singular value decomposition(SVD) method for solving the pass-region problem is proposed. The former can avoid reconstructing errors in time-frequency filtering; the latter is effective to distinguish the pass-region of signal from *** can be realized by removing the smaller singular values and keeping the larger singular values. An additive noise perturbation model is built in ST time-frequency domain and the effective rank of noise perturbation model based on matrix IST is analyzed. Simulation results indicate that the proposed SVD method can provide higher precision than the existing ones at low signal-to-noise ratio and does not need to compute the noise statistics *** examples verify the effectiveness of proposed method.
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