Improved SVD-based technique for enhancing the time-frequency representation of signals

This paper presents an approach for improving the performance of the SVD-based technique enhancing the time-frequency representation of signals previously introduced by the author. The improvement is achieved by two adjustments on the original method. First, the time-frequency representation of the signal is divided into signal subspace and noise subspace using singular values of the matrix as a criterion for space division. Since singular vectors are the span bases of the matrix, reducing the effect of the noise on the singular vectors and using them in reproducing the matrix enhances the information embedded in the time-frequency representation of the signal. The proposed approach utilizes the Savitzkey-Golay low-pass filter for noise attenuation from the singular vectors. This smoothing filter keeps the structure of the existing patterns in the time-frequency representation of the signal as the second improvement.