Hamid Hassanpour - Department of Computer and Electrical Engineering Noushirvani Institute of Technology, University of Mazandaran, Iran
Eshaghi - Department of Computer and Electrical Engineering Noushirvani Institute of Technology, University of Mazandaran, Iran

This paper propose a technique for enhacing the time-frequency representation of signal. Indeed, the paper presents an approach for improving the performance of the SVD- based technique previously introduced by the first author. In the approach 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 noise from 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. The results of applying the proposed method on both on both a synthetic signal and a newborn EEG indicate superiority of the proposed technique over the existing one in enhancing the time-frequency representation of signals.

Signal enhancing , Time - Frequency , Singular value decomposition , EEG