Output-only modal identification has seen significant activity in recent years, especially in
large-scale structures where controlled input force generation is often difficult to achieve …

The book systematically introduces theories of frequently-used modern signal processing
methods and technologies, and focuses discussions on stochastic signal, parameter …

Over the last ten years blind source separation (BSS) has become a prominent processing
tool in the study of human electroencephalography (EEG). Without relying on head modeling …

This paper revisits blind source separation of instantaneously mixed quasi-stationary
sources (BSS-QSS), motivated by the observation that in certain applications (eg, speech) …

Sparsity of signals in the frequency domain is widely used for blind source separation (BSS)
when the number of sources is more than the number of mixtures (underdetermined BSS). In …

In an underdetermined mixture system with n unknown sources, it is a challenging task to
separate these sources from their m observed mixture signals, where mn By exploiting the …

This paper presents a new time-frequency (TF) underdetermined blind source separation
approach based on Wigner-Ville distribution (WVD) and Khatri-Rao product to separate N …

This paper considers the problem of blindly separating sub-and super-Gaussian sources
from underdetermined mixtures. The underlying sources are assumed to be composed of …

Dynamic characteristics of structures—viz. natural frequencies, damping ratios, and mode
shapes—are central to earthquake‐resistant design. These values identified from field …

Herein, we propose a method based on the existing second‐order blind identification of
underdetermined mixtures technique for identifying the modal characteristics—namely …