Applications that operate in highly dynamic environments must deal with real-time changes of circumstances in order to be consistent and coherent. In this work, we propose an exten...
One of the primary advantages of artificial neural networks is their inherent ability to perform massively parallel, nonlinear signal processing. However, the asynchronous dynamics...
We introduce and discuss the application of statistical physics concepts in the context of on-line machine learning processes. The consideration of typical properties of very large...
The aim of this paper is to propose a method for tagging named entities (NE), using natural language processing techniques. Beyond their literal meaning, named entities are freque...
The vulnerability of smart grid systems is a growing concern. Signal detection theory is employed here to detect a change in the system. We employ a discrete-time linear state spa...