Current brain cognitive models are insufficient in handling outliers and dynamics of
electroencephalogram (EEG) signals. This article presents a novel self-paced dynamic …

Data-driven inferential sensor has been widely adopted to estimate key quality relevant
variables. However, industrial dataset usually presents many characteristics such as …

Gaussian mixture models have been widely applied to predict those significant but hard-to-
measure quality variables in industrial processes. However, outliers that result from …

The independent vector analysis (IVA) algorithm employs a multivariate source prior to
retain the dependency between different frequency bins of each source and thereby avoids …

The performance of the independent vector analysis (IVA) algorithm depends on the choice
of the source prior to better model the speech signals as it employs a multivariate source …

In this paper, we propose a robust spectral representation for detecting formants in heavily
degraded conditions. The method combines the temporal robustness of the stabilized …

A novel formant tracker is proposed using the mixture models oft densities (tMMs) for vocal
tract resonance frequencies estimated with a hybrid linear prediction (HLP) method. The …

Formants are major resonances in the vocal tract system. Identification of formants is
important for study of speech. In the literature, formants are typically identified by first …

Independent vector analysis (IVA) is studied as a frequency domain blind source separation
method, which can theoretically avoid the permutation problem by retaining the dependency …

Independent vector analysis (IVA) can theoretically avoid the permutation problem in
frequency domain blind source separation by using a multivariate source prior to retain the …