Reliable recognition of fault type and assessment of fault severity is essential for decision
making in condition-based maintenance of gear transmission systems. In engineering …

With the rapid proliferation of wireless services, the frequency spectrum has become
increasingly crowded, and the interferences and composite signals will be ubiquitous in the …

Providing a broad but in-depth introduction to neural network and machine learning in a
statistical framework, this book provides a single, comprehensive resource for study and …

In the complex gear transmission systems, in wind turbines a crack is one of the most
common failure modes and can be fatal to the wind turbine power systems. A single sensor …

Bounded Component Analysis (BCA) is a recent approach which enables the separation of
both dependent and independent signals from their mixtures. In this approach, under the …

We introduce Polytopic Matrix Factorization (PMF) as a novel data decomposition approach.
In this new framework, we model input data as unknown linear transformations of some …

We introduce a new information maximization (infomax) approach for the blind source
separation problem. The proposed framework provides an information-theoretic perspective …

Aiming at the problem of dependent source separation in complex mechanical systems, the
highly universal frequency-domain convolutive bounded component analysis (FDCBCA) …

Currently, the widely used blind source separation algorithm is typically associated with
issues such as a sluggish rate of convergence and unstable accuracy, and it is mostly …

Amyotrophic lateral sclerosis (ALS) is an incurable neurodegenerative disease in urgent
need of disease biomarkers for the assessment of promising therapeutic candidates in …