In this paper, following the Compressed Sensing (CS) paradigm, we study the problem of recovering sparse or compressible signals from uniformly quantized measurements. We present ...
This paper explores the issues connected to the transmission of three dimensional scenes over unreliable networks such as the wireless ones. It analyzes the effect of the loss of ...
Pietro Zanuttigh, Andrea Zanella, Guido M. Cortela...
This paper presents an experimental implementation of a low-complexity speaker recognition algorithm working in the compressed speech domain. The goal is to perform speaker modeli...
Matteo Petracca, Antonio Servetti, Juan Carlos De ...
In this paper we present a mesh compression method based on a multiresolution decomposition whose detail coefficients have a compact representation and thus smaller entropy than t...
In this paper, we introduce a novel bayesian compressive sensing (CS) technique for phonetic classification. CS is often used to characterize a signal from a few support training...
Tara N. Sainath, Avishy Carmi, Dimitri Kanevsky, B...