S-transform based on compact support kernel

In this paper, the use of a Compact Support Kernel (CSK) instead of the Gaussian window in the S-transform is proposed. The CSK is derived from the Gaussian but overcomes its practical drawbacks while preserving a large number of its useful properties. The width of the CSK is controlled by some parameters making it more flexible. These parameters are selected to optimize the energy concentration in the time-frequency domain. Compared to other versions of S-transform, other time-frequency representations and continuous wavelet transform, the achieved results obtained using synthetic and real data show a significant improvement in the time and frequency resolution, energy concentration and instantaneous frequency estimation.