Abstract. In contrast to the traditional hypothesis-driven methods, independent component analysis (ICA) is commonly used in functional magnetic resonance imaging (fMRI) studies to...
Abstract: The Principal Component Analysis (PCA) is a data dimensionality reduction technique well-suited for processing data from sensor networks. It can be applied to tasks like ...
A fundamental problem in neural network research, as well as in many other disciplines, is finding a suitable representation of multivariate data, i.e. random vectors. For reasons...
Software metrics is vital for the management of software development, especially when a new technology is adopted and established practices have yet to be developed. As a kind of s...
Embedded systems have several characteristics, such as application specific needs, real-time constraints and intrinsic embedded concerns (i.e. energy consumption), which hinder th...
Edison Pignaton de Freitas, Marco A. Wehrmeister, ...