Sökning: "Kommunikationsnätverk"
Visar resultat 1 - 5 av 10 avhandlingar innehållade ordet Kommunikationsnätverk.
1. Resource-Constrained Embedded Control and Computing Systems
Sammanfattning : This thesis deals with methods for handling resource constraints in embedded control systems and real-time computing systems. By dynamic feedback-based resource scheduling it is possible to achieve adaptability andincreased performance for these systems. LÄS MER
2. High Frequency Microwave and Antenna Devices based on Transformation Optics and Glide-Symmetric Metasurfaces
Sammanfattning : The new generation of wireless communication networks intends to support data rate of Gbit/s. One solution to make it possible is to move upwards in frequency range to employ the unused spectrum in mm-wave frequencies. LÄS MER
3. Energy Saving vs. Performance: Trade-offs in Optical Networks
Sammanfattning : The energy consumption of communication networks is continuously growing. Many energy saving approaches have been proposed at the device, system, and network level. The most promising way to address this problem is to utilize photonic technologies as much as possible thanks to their low energy consumption per bit performance. LÄS MER
4. First-Order Algorithms for Communication Efficient Distributed Learning
Sammanfattning : Innovations in numerical optimization, statistics and high performance computing have enabled tremendous advances in machine learning algorithms, fuelling applications from natural language processing to autonomous driving.To deal with increasing data volumes, and to keep the training times of increasingly complex machine learning models reasonable, modern optimization algorithms distribute both data and computations over a large number of machines. LÄS MER
5. First-Order Algorithms for Communication Efficient Distributed Learning
Sammanfattning : Technological developments in devices and storages have made large volumes of data collections more accessible than ever. This transformation leads to optimization problems with massive data in both volume and dimension. LÄS MER