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tfg_domenech_gutierrez_xenia.pdf (1.86 MB)

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Bachelor thesis

Publication date

2022-01-24

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cc-by-nc-nd (c) Xènia Domènech Gutiérrez, 2022
Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/187760

Modularization of reservoir computing networks for the recognition of brainstates

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Abstract

[en] This project consisted of the research, study and modularization of a complex neural network, consisting of one or several reservoir computing modules. This is performed by means of Python scripts, aiming at learning in a way inspired on how the human brain does. The manucript starts with a theoretical introduction describing basic concepts of complex networks, listing their types and applications, so that the reader can understand how we have used the idea for the development of the script. The second part describes the process and impact of the modularization modules first described, and the comparison with the non-modularized program.

Description

Treballs Finals de Grau de Matemàtiques, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2022, Director: Ignasi Cos Aguilera i Gorka Zamora López

Subject

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

Subject (English)

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

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Treballs Finals de Grau (TFG) - Matemàtiques

Citation

DOMÈNECH GUTIÉRREZ, Xènia. Modularization of reservoir computing networks for the recognition of brainstates. [consulta: 12 de maig de 2026]. Disponible a: https://hdl.handle.net/2445/187760

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