Sökning: "real-world network data"
Visar resultat 11 - 15 av 186 uppsatser innehållade orden real-world network data.
11. Comparing energy efficiency of Leaky integrate-and-fire and Spike response neuron models in Spiking Neural Networks
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Spiking Neural Networks (SNNs) are a type of neural network that is designed to mimic the way neurons function in our brains. While there have been notable advancements in developing SNNs, energy consumption hasn't been studied to the same extent. This gets especially relevant with steadily increasing network sizes. LÄS MER
12. Causal Discovery for Time Series : Based on Continuous Optimization
Uppsats för yrkesexamina på avancerad nivå, Luleå tekniska universitet/Institutionen för system- och rymdteknikSammanfattning : Causal discovery is an important field of study that seeks to understand the underlying relationships between variables in a system. The goal of causal discovery is to discover the causal relationships from observational data and determine the direction of influence between variables. LÄS MER
13. Cyber Threat Detection using Machine Learning on Graphs : Continuous-Time Temporal Graph Learning on Provenance Graphs
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Cyber attacks are ubiquitous and increasingly prevalent in industry, society, and governmental departments. They affect the economy, politics, and individuals. LÄS MER
14. Simulation and Testing of a MU-MIMO Beamforming System
Master-uppsats, Lunds universitet/Institutionen för elektro- och informationsteknikSammanfattning : Multi-User Multiple-Input Multiple-Output (MU-MIMO) technology has become increasingly important in the field of wireless communication due to its ability to highly increase the capacity and efficiency of wireless networks [1]. Beamforming, as a technique used in MU-MIMO systems, improves network performance by improving signal quality and reducing interference. LÄS MER
15. Neural Networks for Predictive Maintenance on Highly Imbalanced Industrial Data
Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskapSammanfattning : Preventive maintenance plays a vital role in optimizing industrial operations. However, detecting equipment needing such maintenance using available data can be particularly challenging due to the class imbalance prevalent in real-world applications. LÄS MER