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—Radio Frequency Energy harvesting is a research topic of increasing interest, related to sustainability, which could become a promising alternative to existing energy resources. The paper will show all the activities addressed to design a wideband system to recover wideband energy from electromagnetic sources present in the environment. The main idea is to(More)
In modeling time series, convolution multi-layer graphs are able to capture long-term dependence at a gradually increasing scale. We present an approach to learn a layered factor graph architecture starting from a stationary latent models for each layer. Simulations of belief propagation are reported for a three-layer graph on a small data set of characters.
We propose a Multi-Layer Network based on the Bayesian framework of the Factor Graphs in Reduced Normal Form (FGrn) applied to a two-dimensional lattice. The Latent Variable Model (LVM) is the basic building block of a quadtree hierarchy built on top of a bottom layer of random variables that represent pixels of an image, a feature map, or more generally a(More)
The paper deals with the implementation of a suitable technological support to improve the success likelihood of Urban Search and Rescue (USAR) missions. In particular, the adoption of an heterogeneous sensors network for situation awareness and security applications is suggested. The sensor network consists of two types of sensor, mandated, respectively,(More)
We build a multi-layer architecture using the Bayesian framework of the Factor Graphs in Reduced Normal Form (FGrn). This model allows great modularity and unique localized learning equations. The multi-layer architecture implements a hierarchical data representation that via belief propagation can be used for learning and inference in pattern completion,(More)
We apply belief propagation to a Bayesian bipartite graph composed of discrete independent hidden variables and discrete visible variables. The network is the Discrete counterpart of Independent Component Analysis (DICA) and it is manipulated in a factor graph form for inference and learning. A full set of simulations is reported for character images from(More)
The development of intelligent surveillance systems is an active research area. In this context, mobile and multifunctional robots have been recently adopted as successful means to reduce fixed installations and the number of devices needed to cover a given area. On the other hand, modern techniques for data fusion and decision making can significantly(More)
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