Condition-based maintenance is becoming increasingly important in hydraulic systems.
However, anomaly detection for these systems remains challenging, especially since that …

We propose sparse representation and dictionary learning algorithms for dictionaries whose
atoms are characterized by Gaussian probability distributions around some central atoms …

Realizing sufficient separability between the distributions of healthy and pathological
samples is a critical obstacle for pathology detection convolutional models. Moreover, these …

We propose an extension of the Angle-Based Outlier Detection (ABOD) technique by
combining it with a Dictionary Learning (DL) problem. The ABOD method benefits from this …

In this paper we present new algorithms for training reduced-size nonlinear representations
in the Kernel Dictionary Learning (KDL) problem. Standard KDL has the drawback of a large …