Sökning: "Sparse Dictionary Learning"
Visar resultat 1 - 5 av 7 uppsatser innehållade orden Sparse Dictionary Learning.
1. Deep Neural Networks for dictionary-based 5G channel estimation with no ground truth in mixed SNR scenarios
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Channel estimation is a fundamental task for exploiting the advantages of massive Multiple-Input Multiple-Output (MIMO) systems in fifth generation (5G) wireless technology. Channel estimates require solving sparse linear inverse problems that is usually performed with the Least Squares method, which brings low complexity but high mean squared error values. LÄS MER
2. Sparse Approximation of Spatial Channel Model with Dictionary Learning
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : In large antenna systems, traditional channel estimation is costly and infeasible in some situations. Compressive sensing was proposed to estimate the channel with fewer measurements. Most of the previous work uses a predefined discrete Fourier transform matrix or overcomplete Fourier transform matrix to approximate the channel. LÄS MER
3. Hand Gesture Classification using Millimeter Wave Pulsed Radar
Master-uppsats, Lunds universitet/Matematisk statistikSammanfattning : Millimeter wave pulsed radar has found many applications, among them hand gesture sensing, which this work has as purpose. This application has already shown good potential, [1], and here in this work robustness aspects are taken into account. LÄS MER
4. Outlier detection on sparse-encoded vibration signals from rolling element bearings
Uppsats för yrkesexamina på avancerad nivå, Luleå tekniska universitet/Institutionen för system- och rymdteknikSammanfattning : The demand for reliable condition monitoring systems on rotating machinery for power generation is continuously increasing due to a wider use of wind power as an energy source, which requires expertise in the diagnostics of these systems. An alternative to the limited availability of diagnostics and maintenance experts in the wind energy sector is to use unsupervised machine learning algorithms as a support tool for condition monitoring. LÄS MER
5. Zedboard based platform for condition monitoring and control experiments
Kandidat-uppsats, Luleå tekniska universitet/Institutionen för system- och rymdteknikSammanfattning : New methods for monitoring the condition of roller element bearings in rotating machinery offer possibilities to reduce repair- and maintenance costs, and reduced use of environmentally harmful lubricants. One such method is sparse representation of vibration signals using matching pursuit with dictionary learning, which so far has been tested on PCs with data from controlled tests. LÄS MER