Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/119796
Title: Study of reconstruction ICA for feature extraction in images and signals
Author: Beltrán Segarra, Marc
Director/Tutor: Igual Muñoz, Laura
Keywords: Xarxes neuronals (Informàtica)
Aprenentatge automàtic
Programari
Treballs de fi de grau
Algorismes computacionals
Neural networks (Computer science)
Machine learning
Computer software
Bachelor's thesis
Computer algorithms
Issue Date: 22-Jun-2017
Abstract: [en] During the last years, neural networks have become a vehicular discipline in the field of machine learning. At the same time, classical machine learning methods have become easier to use due to the availability of higher computational power. The goal of this project is to reconstruct a classical machine learning algorithm used for feature and source extraction (ICA) using neural networks. This reconstruction could bypass some of the drawbacks presents when using ICA. We have studied how the reconstruction operates under different conditions and performed a comparison with the classical algorithm that we reconstructed.
Note: Treballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2017, Director: Laura Igual Muñoz
URI: http://hdl.handle.net/2445/119796
Appears in Collections:Treballs Finals de Grau (TFG) - Enginyeria Informàtica
Programari - Treballs de l'alumnat

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