Artificial neural networks (ANNs) ability to learn, correct errors, and transform a large amount
of raw data into beneficial medical decisions for treatment and care has increased in …

Speech signals observed from distantly placed microphones may have some acoustic
interference, such as noise and reverberation. These may lead to the degradation of the …

Composite fault diagnosis of rolling bearings is very challenging work, especially when the
characteristic frequency ranges of different fault types overlap. To solve this problem, an …

The multichannel variational autoencoder (MVAE) integrates the rule-based update of a
separation matrix and the deep generative model and proves to be a competitive speech …

This paper proposes a novel efficient multistage algorithm to extract source speech signals
from a noisy convolutive mixture. The proposed approach comprises two stages named …

For the problem that traditional methods are difficult to identify bearing composite faults, a
determined convolution blind source separation method based on harmonic vector analysis …

This paper improves the speech amplitude in Bayesian speech enhancement estimation by
introducing a super-Gaussian cardinality distribution probability density function in the filter's …

Aiming at the problem about DOA estimation of a far-field uniform linear array (ULA) under
the framework of blind source separation (BSS), this paper proposes a method based on …

Abstract Blind Source Separation (BSS) application is a delinquent issue in a complex
reverberant environment with changing room geometric dimensions and an increasing …