Despite various speech enhancement techniques have been developed for different applications, existing methods are limited in noisy environments with high ambient noise levels. Speech presence probability (SPP) estimation is a speech enhancement technique to reduce speech distortions, especially in low signalto-noise ratios (SNRs) scenario. In this paper, we propose a new two-dimensional (2D) Teager-energyoperators (TEOs) improved SPP estimator for speech enhancement in time-frequency (T-F) domain. Wavelet packet transform (WPT) as a multiband decomposition technique is used to concentrate the energy distribution of speech components. A minimum mean-square error (MMSE) estimator is obtained based on the generalized gamma distribution speech model in WPT domain. In addition, the speech samples corrupted by environment and occupational noises (i.e., machine shop, factory and station) at different input SNRs are used to validate the proposed algorithm. Results suggest that the proposed method achieves a significant enhancement on perceptual quality, compared with four conventional speech enhancement algorithms (i.e., MMSE-84, MMSE-04, Wiener-96, and BTW).

This paper aims to address the problems of inaccurate location and large computation in hybrid transmission line traveling wave detection methods. In this paper, a new fault location method based on empirical Fourier decomposition (EFD) and the Teager energy operator (TEO) is proposed. Firstly, the combination of EFD and the TEO is used to detect the time difference between the arrival of the initial traveling wave of the fault at the two measurement ends of the hybrid line. Then, when the fault occurs at the midpoint of each line segment and at the connection point of the hybrid line, the time difference between the arrival of the fault traveling wave at the two measurement ends of the line is calculated according to the line parameters. By comparing the obtained time differences, it is determined whether the fault occurs in the first or second half of the line. Finally, the fault distance is calculated using the double-ended traveling wave method according to the fault section. The model was built on PSCAD and the proposed algorithm was simulated on MATLAB platform. The results demonstrate that the proposed method achieves an average fault location accuracy of 98.88% by adjusting transition resistances and fault distances and comparing with other location methods. After validation, the proposed method for locating faults has a high level of accuracy in location, computational efficiency, and reliability. It can accurately identify fault segments and locations in hybrid transmission line systems.