Blar i NTNU Open på forfatter "Nichele, Stefano"
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A new Method of Output from Cellular Automata: The Togglecount Transform
Schjelderup, Terje (Master thesis, 2015)Cellular automata (CAs) are lattices of simple cells, whose states change according to a set of local rules. Applications range from simulating real world systems to a general platform for computation. Within the eld of ... -
An investigation into Cellular Automata: The Self-Modifying Instruction-Based Approach
Glover, Tom (Master thesis, 2015)In this thesis we investigate a method for genotype representation in cellular automata. This method is inspired from gene regulation process in biology and is called self-modification. This is then combined with ... -
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 ... -
Assessment and manipulation of the computational capacity of in vitro neuronal networks through criticality in neuronal avalanches
Heiney, Kristine; Huse Ramstad, Ola; Sandvig, Ioanna; Sandvig, Axel; Nichele, Stefano (Chapter, 2020)In this work, we report the preliminary analysis of the electrophysiological behavior of in vitro neuronal networks to identify when the networks are in a critical state based on the size distribution of network-wide ... -
CA-NEAT: Evolved Compositional Pattern Producing Networks for Cellular Automata Morphogenesis and Replication
Nichele, Stefano; Ose, Mathias Berild; Risi, Sebastian; Tufte, Gunnar (Journal article, 2017)Cellular Automata (CA) are a remarkable example of morphogenetic system, where cells grow and self-organise through local interactions. CA have been used as abstractions of biological development and artificial life. Such ... -
Can Genome Information be used to Guide Evolutionary Search?
Wold, Håkon Hjelde (Master thesis, 2013)Uniform cellular automata have been evolved as phenotypes from zygotes using an extensive rule table as the genotype. This is used to simulate complex systems which could impact future hardware development and programming. ... -
Cellular Automata Transition Rules Represented using Compositional Pattern Producing Network - A novel approach through NeuroEvolution of Augmenting Topologies
Fjermestad, Sindre Sundvall (Master thesis, 2017)A system for developing CPPNs was made specifically for the purpose of use for CAs, through the NEAT methodology. -
Computation-in-Materio: evolving computation with light
Normann, Kristian Fladstad (Master thesis, 2017)Evolution-in-Materio is a research field wherein evolutionary algorithms are used to seek out configurations that allows one to make use of a physical material as a computational device. The reasons for this are to seek ... -
Criticality as a measure of developing proteinopathy in engineered human neural networks
Valderhaug, Vibeke Devold; Heiney, Kristine; Huse Ramstad, Ola; Bråthen, Geir; Kuan, Wei-Li; Nichele, Stefano; Sandvig, Axel; Sandvig, Ioanna (Journal article, 2020)A patterned spread of proteinopathy represents a common characteristic of many neurodegenerative diseases. In Parkinson’s disease (PD), misfolded forms of alpha-synuclein proteins aggregate and accumulate in hallmark ... -
Criticality, Connectivity, and Neural Disorder: A Multifaceted Approach to Neural Computation
Heiney, Kristine; Huse Ramstad, Ola; Fiskum, Vegard; Christiansen, Nicholas; Sandvig, Axel; Nichele, Stefano; Sandvig, Ioanna (Peer reviewed; Journal article, 2021)It has been hypothesized that the brain optimizes its capacity for computation by self-organizing to a critical point. The dynamical state of criticality is achieved by striking a balance such that activity can effectively ... -
Deciphering and emulating neuronal communication: Population-level computation from elemental interactions
Heiney, Kristine (Doctoral theses at NTNU;2023:220, Doctoral thesis, 2023)This thesis explores computation in neural systems and how we might draw inspiration from it in designing computational systems. The research conducted for this thesis encompasses both neural data analysis and computational ... -
Deep learning with cellular automaton-based reservoir computing
Nichele, Stefano; Molund, Andreas (Journal article; Peer reviewed, 2017)Recurrent neural networks (RNNs) have been a prominent concept within artificial intelligence. They are inspired by biological neural networks (BNNs) and provide an intuitive and abstract representation of how BNNs work. ... -
A Deep Learning-Based Tool for Automatic Brain Extraction from Functional Magnetic Resonance Images of Rodents
Gulden Dahl, Annelene; Nichele, Stefano; Mello, Gustavo (Chapter, 2021)Removing skull artifacts from functional magnetic images (fMRI) is a well understood and frequently encountered problem. Because the fMRI field has grown mostly due to human studies, many new tools were developed to handle ... -
Deep Reservoir Computing Using Cellular Automata
Molund, Andreas (Master thesis, 2017)Recurrent Neural Networks (RNNs) is a prominent concept within artificial intelligence. RNNs are inspired by Biological Neural Networks (BNNs) and provide an intuitive representation of how BNNs work. Derived from the more ... -
Early functional changes associated with alpha-synuclein proteinopathy in engineered human neural networks
Valderhaug, Vibeke Devold; Heiney, Kristine; Huse Ramstad, Ola; Bråthen, Geir; Kuan, Wei-Li; Nichele, Stefano; Sandvig, Axel; Sandvig, Ioanna (Peer reviewed; Journal article, 2021)A patterned spread of proteinopathy represents a common characteristic of many neurodegenerative diseases. In Parkinson’s disease (PD), misfolded forms of α-synuclein proteins accumulate in hallmark pathological inclusions ... -
Evading a Machine Learning-based Intrusion Detection System through Adversarial Perturbations
Fladby, Torgeir; Haugerud, Hårek; Nichele, Stefano; Begnum, Kyrre; Yazidi, Anis (Chapter, 2020)Machine-learning based Intrusion Detection and Prevention Systems provide significant value to organizations because they can efficiently detect previously unseen variations of known threats, new threats related to known ... -
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 ... -
Evolvability, Complexity and Scalability of Cellular Evolutionary and Developmental Systems
Nichele, Stefano (Doctoral thesis at NTNU;2015:31, Doctoral thesis, 2015)Man-made systems, such as supercomputers and software, IT-infrastructures and networks of any kind, are continuously growing in size and complexity. As conventional top-down engineering techniques may have reached the ... -
Evolving Cellular Automata in-Materio
Farstad, Sigve Sebastian (Master thesis, 2015)Evolution-in-Materio in the context of unconventional computing is the practice of using artificial evolution techniques to search for configurations of physical material samples that allow for them to be used as practical ... -
Evolving Compositional Pattern Producing Networks For Cellular Automata Transition Rules
Ose, Mathias Berild (Master thesis, 2017)Traditional Cellular Automata (CA) transition rules are encoded as tables that grow quickly when the number of cell states or the size of the CA neighborhood increases. For methods that search for good transition rules, ...