Joint time-frequency analysis: methods and applications
Joint time-frequency analysis: methods and applications
New discrete inverse S transform with least square error in filtering
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Novel inverse S transform with equalization filter
IEEE Transactions on Signal Processing
Localization of the complex spectrum: the S transform
IEEE Transactions on Signal Processing
Comments on “The Inverse S-Transform in Filters With Time-Frequency Localization”
IEEE Transactions on Signal Processing
Authors' Reply to Comments on “The Inverse S-Transform in Filters With Time-Frequency Localization”
IEEE Transactions on Signal Processing
The S-Transform and Its Inverses: Side Effects of Discretizing and Filtering
IEEE Transactions on Signal Processing
The -Transform From a Wavelet Point of View
IEEE Transactions on Signal Processing - Part I
The inverse S-transform in filters with time-frequency localization
IEEE Transactions on Signal Processing
Hi-index | 35.68 |
The S transform is useful in time-frequency analysis. Many inverse S transform algorithms have been proposed with different filtering properties in the time-frequency spectrum. In this paper, the transformation matrices of the S transform and two novel least square inverse algorithms are proposed. The first one minimizes the global mean square error of the entire time-frequency spectrum, and the second one considers only the specific interesting time-frequency regions and is more flexible. The proposed inverse algorithms can provide more stable and better performance than the existing ones.