Browsing NTNU Open by Author "Nichele, Stefano"
Now showing items 21-40 of 49
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Evolving Knowledge And Structure Through Evolution-based Neural Architecture Search
Wang, Magnus Poppe (Master thesis, 2019)Meta learning is a step towards an artificial general intelligence, where neural architecture search is at the forefront. The methods dominating the field of neural architecture search are recurrent neural networks and ... -
Evolving spiking neuron cellular automata and networks to emulate in vitro neuronal activity
Jensen Farner, Jørgen; Weydahl, Håkon; Jahren, Ruben; Huse Ramstad, Ola; Nichele, Stefano; Heiney, Kristine Anne (Chapter, 2021)Neuro-inspired models and systems have great potential for applications in unconventional computing. Often, the mechanisms of biological neurons are modeled or mimicked in simulated or physical systems in an attempt to ... -
A general representation of dynamical systems for reservoir computing
Pontes-Filho, Sidney; Yazidi, Anis; Zhang, Jianhua; Hammer, Hugo Lewi; Mello, Gustavo; Sandvig, I.; Tufte, Gunnar; Nichele, Stefano (Chapter, 2019)Dynamical systems are capable of performing computation in a reservoir computing paradigm. This paper presents a general representation of these systems as an artificial neural network (ANN). Initially, we implement the ... -
Hallmarks of Criticality in Neuronal Networks Depend on Cell Type and the Temporal Resolution of Neuronal Avalanches
Heiney, Kristine; Valderhaug, Vibeke Devold; Huse Ramstad, Ola; Sandvig, Ioanna; Sandvig, Axel; Nichele, Stefano (Peer reviewed; Journal article, 2021)The human brain has a remarkable capacity for computation, and it has been theorized that this capacity arises from the brain self-organizing into the critical state, a dynamical state poised between ordered and dis- ordered ... -
Inkrementell vekst av genomet for evolusjon av genotype representasjoner for kunstige cellulære organismer.
Giskeødegård, Andreas (Master thesis, 2013)I denne avhandlingen utforsker vi mulighetene for utvikling cellulær automat attraktorer i forskjellige størrelser med en algoritme som sakte utvider genotype av individer. Attraktorer av forskjellige størrelser er dyrket ... -
Introducing IoT Competencies to First-Year University Students With The Tiles Toolkit
Mora, Simone; Gianni, Francesco Valerio; Nichele, Stefano; Divitini, Monica (Chapter, 2018)Advances in the field of Internet of Things (IoT) are introducing innovations in multiple domains including smart cities, healthcare and transportation. An increasing number of jobs today require IoT competences that ... -
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 ... -
Investigation of Elementary Cellular Automata for Reservoir Computing
Bye, Emil Taylor (Master thesis, 2016)Reservoir computing is an approach to machine learning. Typical reservoir computing approaches use large, untrained artificial neural networks to transform an input signal. To produce the desired output, a readout layer ... -
Local Delay Plasticity Supports Generalized Learning in Spiking Neural Networks
Farner, Jørgen Jensen; Huse Ramstad, Ola; Nichele, Stefano; Heiney, Kristine (Chapter, 2023)We propose a novel local learning rule for spiking neural networks in which spike propagation times undergo activity-dependent plasticity. Our plasticity rule aligns pre-synaptic spike times to produce a stronger and more ... -
Machine Learning for Gesture Recognition with Electromyography
Chau, Tony (Master thesis, 2017)About 70 million deaf people use sign language as their first language or mother tongue, but the lack of a common language between the deaf and hearing individuals makes the general communication difficult. This thesis ... -
Merging pruning and neuroevolution: towards robust and efficient controllers for modular soft robots
Nadizar, Giorgia; Medvet, Eric; Huse Ramstad, Ola; Nichele, Stefano; Pellegrino, Felice Andrea; Zullich, Marco (Peer reviewed; Journal article, 2022)Artificial neural networks (ANNs) can be employed as controllers for robotic agents. Their structure is often complex, with many neurons and connections, especially when the robots have many sensors and actuators distributed ... -
Method to Obtain Neuromorphic Reservoir Networks from Images of in Vitro Cortical Networks
Mello, Gustavo; Pontes-Filho, Sidney; Sandvig, Ioanna; Valderhaug, Vibeke Devold; Zouganeli, Evi; Huse Ramstad, Ola; Sandvig, Axel; Nichele, Stefano (Chapter, 2020)In the brain, the structure of a network of neurons defines how these neurons implement the computations that underlie the mind and the behavior of animals and humans. Provided that we can describe the network of neurons ... -
Minimum Equivalence in Random Boolean Networks, Elementary Cellular Automata, and Beyond
Glover, Tom Eivind; Jahren, Christian Ruben; Huse Ramstad, Ola; Nichele, Stefano (Chapter, 2023)Random Boolean networks (RBN) and Cellular Automata (CA) operate in a very similar way. They update their state with simple deterministic functions called Boolean function or Transition Table (TT), both being essentially ... -
Motifs of Order: Emergent Self-Organization and Complex Dynamics in Biological Neural Networks
Weir, Janelle Shari (Doctoral theses at NTNU;2024:37, Doctoral thesis, 2024) -
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, ... -
Neuronal avalanche dynamics and functional connectivity elucidate information propagation in vitro
Heiney, Kristine Anne; Huse Ramstad, Ola; Fiskum, Vegard; Sandvig, Axel; Sandvig, Ioanna; Nichele, Stefano (Peer reviewed; Journal article, 2022)Cascading activity is commonly observed in complex dynamical systems, including networks of biological neurons, and how these cascades spread through the system is reliant on how the elements of the system are connected ... -
Optimization of dynamical systems towards criticality and intelligent behavior
Pontes-Filho, Sidney (Doctoral theses at NTNU;2023:57, Doctoral thesis, 2023)With the progress of computing power, artificial intelligence (AI) systems are able to achieve outstanding results that surpass human-level performance on some tasks, such as image recognition. Mainstream AI systems are ... -
Optimizing Bio-Inspired Propulsion Systems using Genetic Algorithms
Gjerde, Thomas (Master thesis, 2017)Optimization is an important part of the development of an efficient propulsion system. The biomimetic marine propulsion system referred to as an oscillating foil has recently seen an upswing in interest. The optimization ... -
Optimizing for Energy in High-Level Programming Languages on Embedded Devices
Gombos, Péter Henrik (Master thesis, 2015)The use of embedded systems has exploded recently, and thus also the number of developers for embedded systems. But the traditional way of programming embedded computers is hard and error prone, and the use of high-level ... -
Reducing the Search Space of Neuroevolution using Monte Carlo Tree Search
Wiker, Erik (Master thesis, 2019)Denne oppgaven undersøker muligheten for å bruke Monte-Carlo-tre-søk for å redusere søkeområdet til den velkjente maskinlæringsalgoritmen Neuroevolution of Augmenting Topologies, med sikte på å oppnå kortere kjøretider og ...