Publications by Lorenzo Granai

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Low bit rate image coding is an important problem regarding applications such as storage on low memory devices or streaming data on the internet. The state of the art in image compression is to use 2-D wavelets. The advantages of wavelet bases lie in their ...

The problem of efficiently representing and approximating digital data is an open challenge and it is of paramount importance for many applications. This dissertation focuses on the approximation of natural signals as an organized combination of mutually c ...

This paper explores a novel approach for ventricular and atrial activities estimation in electrocardiogram (ECG) signals, based on sparse source separation. Sparse decompositions of ECG over signal-adapted multi-component dictionaries can lead to natural s ...

Given the increasing popularity of real-time video communication over enterprise wireless networks, ensuring good quality of experience is becoming critical. A common problem in such networks is that the clients typically adopt the strategy of associating ...

Recent results have underlined the importance of incoherence in redundant dictionaries for a good behavior of decomposition algorithms like Matching and Basis Pursuits. However, appropriate dictionaries for a given application may not necessarily be able t ...

Lorenzo Granai

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Image compression using an edge adapted redundant dictionary and wavelets

Nonlinear approximation with redundant multi-component dictionaries

Ventricular and Atrial Activity Estimation Through Sparse ECG Signal Decompositions

Load Balancing Video Clients in Enterprise Wireless Networks

On the Use of A Priori Information for Sparse Signal Approximations