Traditional approaches to channel equalization are based on the inversion of the global (linear or nonlinear) channel response. However, in digital links the complete channel inve...
Mirko Solazzi, Aurelio Uncini, Elio D. Di Claudio,...
In this work new Decision-Feedback (DF) Neural Equalizers (DFNE) are introduced and compared with classical DF equalizers and Viterbi demodulators. It is shown that the choice of ...
Elio D. Di Claudio, Raffaele Parisi, Gianni Orland...
Most existing content-based filtering approaches including Rocchio, Language Models, SVM, Logistic Regression, Neural Networks, etc. learn user profiles independently without ca...
Based on rank-1 update, Sparse Bayesian Learning Algorithm (SBLA) is proposed. SBLA has the advantages of low complexity and high sparseness, being very suitable for large scale pr...
In this paper we show that generative models are competitive with and sometimes superior to discriminative models, when both kinds of models are allowed to learn structures that a...