Independent component analysis (ICA) is a statistical method for transforming an observable
multi-dimensional random vector into components that are as statistically independent as …

Signals and Images: Advances and Results in Speech, Estimation, Compression,
Recognition, Filtering, and Processing cohesively combines contributions from field experts …

An interesting and recent application of population-based metaheuristics resides in an
unsupervised signal processing task: independent component analysis (ICA) over finite …

This is the second part of the introductory tutorial about information theoretic learning, which,
after the theoretical foundations presented in Part I, now discusses the concepts of …

Independent component analysis (ICA) is a statistical method for transforming an observable
multi-dimensional random vector into components that are as statistically independent as …

In communication systems, the study of elements and structures defined over Galois fields
are generally limited to data coding. However, in this work, a novel perspective that …

The problem of blind source separation (BSS) has been intensively studied by the signal
processing community. The first solutions to deal with BSS were proposed in the 1980's and …

Recentemente, algoritmos de Análise de Componentes Independentes (ICA) em alfabetos
finitos foram propostos. Tendo em vista cenários não-testados e a replicação de resultados …

Optimization problems such as the Uncapacitated Single-Allocation p-Hub Median Problem
represent good models for real network design issues, hence an increasing research …

Signal processing is a broader field than it may seem prima facie. Essentially, it is related to
the notion of using a specially designed system (which will be termed filter) to mold an input …