TITLE:
Non-Stationary Signal Segmentation and Separation from Joint Time-Frequency Plane
AUTHORS:
Abdullah Ali Alshehri
KEYWORDS:
Signal Segmentation; Time-Frequency Distribution; Short-Time Fourier Transform; Non-Stationary; Wiener Masking
JOURNAL NAME:
Journal of Signal and Information Processing,
Vol.3 No.3,
August
31,
2012
ABSTRACT: Multi-components sinusoidal engineering signals who are non-stationary signals were considered in this study since their separation and segmentations are of great interests in many engineering fields. In most cases, the segmentation of non-stationary or multi-component signals is conducted in time domain. In this paper, we explore the advantages of applying joint time-frequency (TF) distribution of the multi-component signals to identify their segments. The Spectrogram that is known as Short-Time Fourier Transform (STFT) will be used for obtaining the time-frequency kernel. Time marginal of the computed kernel is optimally used for the signal segmentation. In order to obtain the desirable segmentation, it requires first to improve time marginal of the kernel by using two-dimensional Wiener mask filter applied to the TF kernel to mitigate and suppress non-stationary noise or interference. Additionally, a proper choice of the sliding window and its overlaying has enhanced our scheme to capture the discontinuities corresponding to the boundaries of the candidate segments.