Abstract
A Simulink Library for rapid prototyping of belief network architectures using Forney-style Factor Graph is presented. Our approach allows to draw complex architectures in a fairly easy way giving to the user the high flexibility of Matlab-Simulink environment. In this framework the user can perform rapid prototyping because belief propagation is carried in a bi-directional data flow in the Simulink architecture. Results on learning a latent model for artificial characters recognition are presented.
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Buonanno, A., Palmieri, F.A.N. (2015). Simulink Implementation of Belief Propagation in Normal Factor Graphs. In: Bassis, S., Esposito, A., Morabito, F. (eds) Advances in Neural Networks: Computational and Theoretical Issues. Smart Innovation, Systems and Technologies, vol 37. Springer, Cham. https://doi.org/10.1007/978-3-319-18164-6_2
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DOI: https://doi.org/10.1007/978-3-319-18164-6_2
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-18163-9
Online ISBN: 978-3-319-18164-6
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