Browsing NTNU Open by Author "Lind, Pedro"
Now showing items 1-11 of 11
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Assessing the robustness of critical behavior in stochastic cellular automata
Pontes Filho, Sidney; Lind, Pedro; Nichele, Stefano (Peer reviewed; Journal article, 2022)There is evidence that biological systems, such as the brain, work at a critical regime robust to noise, and are therefore able to remain in it under perturbations. In this work, we address the question of robustness of ... -
Comparative Analysis of Functional Connectivity Metrics in EEG Datasets
Maratova, Assem; Lencastre, Pedro; Yazidi, Anis; Lind, Pedro (Journal article, 2023)Analysis of functional connectivity helps to determine how brain regions interact with one another and to understand neurological diseases better. In this study, we compare functional connectivity networks derived from ... -
EvoDynamic: A Framework for the Evolution of Generally Represented Dynamical Systems and Its Application to Criticality
Pontes-Filho, Sidney; Lind, Pedro; Yazidi, Anis; Zhang, Jianhua; Hammer, Hugo Lewi; Mello, Gustavo; Sandvig, Ioanna; Tufte, Gunnar; Nichele, Stefano (Chapter, 2020)Dynamical systems possess a computational capacity that may be exploited in a reservoir computing paradigm. This paper presents a general representation of dynamical systems which is based on matrix multiplication. That ... -
Exploring Interpretable AI Methods for ECG Data Classification
Ojha, Jaya; Haugerud, Hårek; Yazidi, Anis; Lind, Pedro (Chapter, 2024)We address ECG data classification, using methods from explainable artificial intelligence (XAI). In particular, we focus on the extended performance of the ST-CNN-5 model compared to established models. The model showcases ... -
Investigating Rules and Parameters of Reservoir Computing with Elementary Cellular Automata, with a Criticism of Rule 90 and the Five-Bit Memory Benchmark
Glover, Tom Eivind; Lind, Pedro; Yazidi, Anis; Osipov, Evgeny; Nichele, Stefano (Journal article; Peer reviewed, 2023)Reservoir computing with cellular automata (ReCAs) is a promising concept by virtue of its potential for effective hardware implementation. In this paper, we explore elementary cellular automata rules in the context of ... -
Modeling Wind-Speed Statistics beyond the Weibull Distribution
Lencastre, Pedro; Yazidi, Anis; Lind, Pedro (Journal article; Peer reviewed, 2024)While it is well known that the Weibull distribution is a good model for wind-speed measurements and can be explained through simple statistical arguments, how such a model holds for shorter time periods is still an open ... -
Modern AI versus century-old mathematical models: How far can we go with generative adversarial networks to reproduce stochastic processes?
Rego Lencastre e Silva, Pedro; Gjersdal, Marit; Gorjão, Leonardo Rydin; Yazidi, Anis; Lind, Pedro (Peer reviewed; Journal article, 2023)The usage of generative adversarial networks (GAN)s for synthetic time-series data generation has been gaining popularity in recent years with applications from finance to music composition and processing of textual content. ... -
A neuro-inspired general framework for the evolution of stochastic dynamical systems: Cellular automata, random Boolean networks and echo state networks towards criticality
Pontes-Filho, Sidney; Lind, Pedro; Yazidi, Anis; Zhang, Jianhua; Hammer, Hugo Lewi; Mello, Gustavo; Sandvig, Ioanna; Tufte, Gunnar; Nichele, Stefano (Peer reviewed; Journal article, 2020)Although deep learning has recently increased in popularity, it suffers from various problems including high computational complexity, energy greedy computation, and lack of scalability, to mention a few. In this paper, ... -
A new decision making model based on Rank Centrality for GDM with fuzzy preference relations
Yazidi, Anis; Ivanovska, Magdalena; Zennaro, Fabio Massimo; Lind, Pedro; Viedma, Enrique Herrera (Peer reviewed; Journal article, 2021)Preference aggregation in Group Decision Making (GDM) is a substantial problem that has received a lot of research attention. Decision problems involving fuzzy preference relations constitute an important class within GDM. ... -
Predicting missing pairwise preferences from similarity features in group decision making
Abolghasemi, Roza; Khadka, Rabindra; Lind, Pedro; Engelstad, Paal E.; Viedma, Enrique Herrera; Yazidi, Anis (Peer reviewed; Journal article, 2022)In group decision-making (GDM), fuzzy preference relations (FPRs) refer to pairwise preferences in the form of a matrix. Within the field of GDM, the problem of estimating missing values is of utmost importance, since many ... -
Trustworthy machine learning in the context of security and privacy
Upreti, Ramesh; Lind, Pedro; Elmokashfi, Ahmed; Yazidi, Anis (Peer reviewed; Journal article, 2024)Artificial intelligence-based algorithms are widely adopted in critical applications such as healthcare and autonomous vehicles. Mitigating the security and privacy issues of AI models, and enhancing their trustworthiness ...