Sökning: "self-organized criticality"
Visar resultat 1 - 5 av 6 uppsatser innehållade orden self-organized criticality.
1. Exploring time-extended complexity measures in magnetic systems
L3-uppsats, Uppsala universitet/MaterialteoriSammanfattning : Complexity, a fundamental concept in physics, encompasses phenomena spanning atomic to cosmic scales. The natural emergence of complexity can be explained by self-organized criticality. In this work, two complexity measures in magnetic systems are explored. LÄS MER
2. Quantifying the Impact of Synaptic Delay and Neuronal Refractory Period on Criticality in Hierarchical Modular Neural Networks
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Self-organized brain criticality suggests that the brain is able to operate near a critical point.With compelling evidence supporting the theory, it is important to understand whichbiological mechanisms are required for critical dynamics to occur. LÄS MER
3. Study of Generalizations of the Discrete Bak-Sneppen Model
Kandidat-uppsats, Lunds universitet/Matematisk statistikSammanfattning : In 1993, Per Bak and Kim Sneppen proposed a model of co-evolution between species, where survival of a particular species affects the survival of its neighbouring species. In the discrete case of the model, each species, or an entry in a set with periodic boundary conditions, is an element x_i ∈ {0, 1}, in the set of size N, where x_i represents the fitness. LÄS MER
4. Cellular automata analysis of life as a complex physical system
Kandidat-uppsats, Lunds universitet/Matematisk fysik; Lunds universitet/Fysiska institutionenSammanfattning : This thesis regards the study of cellular automata, with an outlook on biological systems. Cellular automata are non-linear discrete mathematical models that are based on simple rules defining the evolution of a cell, depending on its neighborhood. LÄS MER
5. Critical Branching Regulation of the E-I Net Spiking Neural Network Model
Uppsats för yrkesexamina på grundnivå, Luleå tekniska universitet/Institutionen för teknikvetenskap och matematikSammanfattning : Spiking neural networks (SNN) are dynamic models of biological neurons, that communicates with event-based signals called spikes. SNN that reproduce observed properties of biological senses like vision are developed to better understand how such systems function, and to learn how more efficient sensor systems can be engineered. LÄS MER