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Visar resultat 1 - 5 av 37 uppsatser som matchar ovanstående sökkriterier.
1. Over-the-Air Federated Learning with Compressed Sensing
Master-uppsats, Linköpings universitet/KommunikationssystemSammanfattning : The rapid progress with machine learning (ML) technology has solved previously unsolved problems, but training these ML models requires ever larger datasets and increasing amounts of computational resources. One potential solution is to enable parallelization of the computations and allow local processing of training data in distributed nodes, such as Federated Learning (FL). LÄS MER
2. Standardized Test Methods in Over-the-Air Chambers for FCC Part 27
Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för fysikSammanfattning : Base stations (BSs) are the cornerstone that enables wireless communications. In order for a new BS variant to be imported and sold in the US they are required to undergo electromagnetic compatibility (EMC) testing. This testing is necessary to obtain their Federal Communications Commission (FCC) certification. LÄS MER
3. 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
4. Function Computation via Over-the-Air Computation: Practical System Design
Master-uppsats, Uppsala universitet/Institutionen för informationsteknologiSammanfattning : Future wireless networks will need to contain millions of nodes, machines, and devices and provide high-speed and low-latency communication services. The traditional wireless network architecture design separates the communication and computation process, which has low utilization of wireless resources. LÄS MER
5. Edge Machine Learning for Wildlife Conservation : A part of the Ngulia project
Master-uppsats, Linköpings universitet/ReglerteknikSammanfattning : The prominence of Edge Machine Learning is increasing swiftly as the performance of microcontrollers continues to improve. By deploying object detection and classification models on edge devices with camera sensors, it becomes possible to locate and identify objects in their vicinity. LÄS MER