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Bachelor thesis

Publication date

2017-06-22

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memòria: cc-by-nc-sa (c) Marc Beltrán Segarra, 2017
Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/119796

Study of reconstruction ICA for feature extraction in images and signals

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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.

Description

Treballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2017, Director: Laura Igual Muñoz

Subject

Xarxes neuronals (Informàtica), Aprenentatge automàtic, Programari, Treballs de fi de grau, Algorismes computacionals

Subject (English)

Neural networks (Computer science), Machine learning, Computer software, Bachelor's theses, Computer algorithms

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Treballs Finals de Grau (TFG) - Enginyeria Informàtica
Programari - Treballs de l'alumnat

Citation

BELTRÁN SEGARRA, Marc. Study of reconstruction ICA for feature extraction in images and signals. [consulted: 13 of June of 2026]. Available at: https://hdl.handle.net/2445/119796

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