Hyperspectral imaging analysis aims at the estimation of the number of constituent substances, known as endmembers, their spectral signatures as well as their abundance fractions ...
In the last decades, a number of robust fuzzy clustering algorithms have been proposed to partition data sets affected by noise and outliers. Robust fuzzy C-means (robust-FCM) is c...
Mario G. C. A. Cimino, Graziano Frosini, Beatrice ...
Commonly used speech enhancement algorithms estimate the power spectral density of the noise to be removed, or make a decision about the presence of speech in a particular frame, ...
In the presence of a heavy-tail noise distribution, regression becomes much more di cult. Traditional robust regression methods assume that the noise distribution is symmetric and...
In this paper, we investigate the noise robustness of Wang and Shamma's early auditory (EA) model for the calculation of an auditory spectrum in audio classification applicati...