Understanding the structure of multidimensional patterns, especially in unsupervised case, is of fundamental importance in data mining, pattern recognition and machine learning. Se...
We incorporate auditory-based features into an unconventional pattern classification system, consisting of a network of spiking neurones with dynamical and multiplicative synapse...
The increasing amount and complexity of data in toxicity prediction calls for new approaches based on hybrid intelligent methods for mining the data. This focus is required even mo...
Emilio Benfenati, Paolo Mazzatorta, Daniel Neagu, ...
An algorithm is proposed which automatically estimates the local signalto-noise ratio (SNR) between speech and noise. The feature extraction stage of the algorithm is motivated by...
Dimensionality reduction is an important problem in pattern recognition. There is a tendency of using more and more features to improve the performance of classifiers. However, not...