Numerous signals arising from physiological and physical processes, in addition to being non-stationary, are moreover a mixture of sustained oscillations and non-oscillatory …
I Bayram, IW Selesnick - IEEE transactions on signal …, 2009 - ieeexplore.ieee.org
The dyadic wavelet transform is an effective tool for processing piecewise smooth signals; however, its poor frequency resolution (its low Q-factor) limits its effectiveness for processing …
Y Huang, K Tian, A Wu, G Zhang - Journal of ambient intelligence and …, 2019 - Springer
The speech emotion recognition accuracy of prosody feature and voice quality feature declines with the decrease of signal to noise ratio (SNR) of speech signals. In this paper, we …
IW Selesnick - Wavelets and Sparsity XIV, 2011 - spiedigitallibrary.org
The tunable Q-factor wavelet transform (TQWT) is a fully-discrete wavelet transform for which the Q-factor, Q, of the underlying wavelet and the asymptotic redundancy (over-sampling …
Y Bian, B Mercer - IEEE transactions on geoscience and remote …, 2010 - ieeexplore.ieee.org
In this paper, two interferometric SAR (InSAR) phase-filtering methods are proposed. These methods are performed in the wavelet domain and employ the simultaneous detection and …
Y Huang, A Wu, G Zhang, Y Li - IET Signal Processing, 2015 - Wiley Online Library
In this paper, a wavelet packet (WP)‐based acoustic feature extraction approach is proposed for automatic speech emotion recognition (SER). First, the issue of optimising the …
RK Dubey, A Kumar - IET Signal Processing, 2015 - Wiley Online Library
A multi‐resolution framework using auditory perception‐based wavelet packet transform is invoked in multi‐resolution auditory model (MRAM) and used for non‐intrusive objective …
T Feng, Y Sun, Y Wang, P Zhou, H Guo, N Liu - Applied Acoustics, 2019 - Elsevier
Definition of sound feature space affects the performance of a sound quality evaluation (SQE) model. In this paper, two types of sound feature space, which consider …