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pro vyhledávání: '"Letizia, Nunzio A."'
Estimating mutual information accurately is pivotal across diverse applications, from machine learning to communications and biology, enabling us to gain insights into the inner mechanisms of complex systems. Yet, dealing with high-dimensional data p
Externí odkaz:
http://arxiv.org/abs/2305.20025
In this paper, the problem of determining the capacity of a communication channel is formulated as a cooperative game, between a generator and a discriminator, that is solved via deep learning techniques. The task of the generator is to produce chann
Externí odkaz:
http://arxiv.org/abs/2305.13493
Autor:
Letizia, Nunzio A., Tonello, Andrea M.
Probability density estimation from observed data constitutes a central task in statistics. Recent advancements in machine learning offer new tools but also pose new challenges. The big data era demands analysis of long-range spatial and long-term te
Externí odkaz:
http://arxiv.org/abs/2211.15353
Autor:
Tonello, Andrea M., Letizia, Nunzio A.
We are assisting at a growing interest in the development of learning architectures with application to digital communication systems. Herein, we consider the detection/decoding problem. We aim at developing an optimal neural architecture for such a
Externí odkaz:
http://arxiv.org/abs/2205.07061
Autor:
Letizia, Nunzio A., Tonello, Andrea M.
The development of optimal and efficient machine learning-based communication systems is likely to be a key enabler of beyond 5G communication technologies. In this direction, physical layer design has been recently reformulated under a deep learning
Externí odkaz:
http://arxiv.org/abs/2111.07606
Autor:
Letizia, Nunzio A., Tonello, Andrea M.
Channel capacity plays a crucial role in the development of modern communication systems as it represents the maximum rate at which information can be reliably transmitted over a communication channel. Nevertheless, for the majority of channels, find
Externí odkaz:
http://arxiv.org/abs/2107.03084
Autor:
Letizia, Nunzio A., Tonello, Andrea M.
The autoencoder concept has fostered the reinterpretation and the design of modern communication systems. It consists of an encoder, a channel, and a decoder block which modify their internal neural structure in an end-to-end learning fashion. Howeve
Externí odkaz:
http://arxiv.org/abs/2009.05273
A great deal of attention has been recently given to Machine Learning (ML) techniques in many different application fields. This paper provides a vision of what ML can do in Power Line Communications (PLC). We firstly and briefly describe classical f
Externí odkaz:
http://arxiv.org/abs/1904.11949
The accurate estimation of the mutual information is a crucial task in various applications, including machine learning, communications, and biology, since it enables the understanding of complex systems. High-dimensional data render the task extreme
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::32f192001b9f1919666ce8e7308e13c7
http://arxiv.org/abs/2305.20025
http://arxiv.org/abs/2305.20025
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