Sökning: "Feed Forward Neural Networks"

Visar resultat 16 - 20 av 57 uppsatser innehållade orden Feed Forward Neural Networks.

1. 16. Unsupervised learning of data representations in brain-like neural networks

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Arian Javdan; [2021]
   Nyckelord :;

   Sammanfattning : Recently, there has been a growing interest in brain-plausible neural networks that closely resemble the brain’s structure. However, conventional networks do not make good models for the brain since these connections are modelled differently, hence the interest in brain-plausible networks. LÄS MER

3. 17. PREDICTION OF WIND TURBINE BLADE FATIGUE LOADS USING FEED-FORWARD NEURAL NETWORKS

   Master-uppsats, Uppsala universitet/Institutionen för geovetenskaper

   Författare :Mohammad Mehdi Mohammadi; [2021]
   Nyckelord :Machine Learning; Feed-Forward Artificial Neural Network; Wind Power; Damage Equivalent Loads; Fatigue; Wind Turbine Blades; NEWA Data; SCADA; Lillgrund Wind Farm;

   Sammanfattning : In recent years, machine learning applications have gained great attention in the wind power industry. Among these, artificial neural networks have been utilized to predict the fatigue loads of wind turbine components such as rotor blades. LÄS MER

4. 18. Determining linguistic predictor for the classification of subjective cognitive impairment and mild cognitive impairment using machine learning

   Master-uppsats, Göteborgs universitet / Institutionen för filosofi, lingvistik och vetenskapsteori

   Författare :Tian Wang; [2020-09-01]
   Nyckelord :mild cognitive impairment; sibjective cognitive impairment; natural language processing; support vector machine; neural networks;

   Sammanfattning : Introduction Mild Cognitive Impairment (MCI) is a neurological condition characterized by cognitive decline greater than expected for an individual's age and education level. Subjective Cognitive Impairment (SCI) is a selfreported decline in cognitive abilities but not clinically identified as MCI. LÄS MER

5. 19. A Study of the Loss Landscape and Metastability in Graph Convolutional Neural Networks

   Master-uppsats, KTH/Matematisk statistik

   Författare :Sofia Larsson; [2020]
   Nyckelord :Graph neural networks; Graph convolutional neural networks; Loss landscape; Gradient descent; Stochastic gradient descent; Stochastic gradient Langevin dynamics; Grafneurala nätverk; grafiska faltningsnätverk; lösningslandskap; gradientmetoder; stokastiska gradientmetoder; stokastisk gradient Langevin dynamik;

   Sammanfattning : Many novel graph neural network models have reported an impressive performance on benchmark dataset, but the theory behind these networks is still being developed. In this thesis, we study the trajectory of Gradient descent (GD) and Stochastic gradient descent (SGD) in the loss landscape of Graph neural networks by replicating Xing et al. LÄS MER

7. 20. Machine Learning Uplink Power Control in Single Input Multiple Output Cell-free Networks

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Yiyang Tai; [2020]
   Nyckelord :Neural networks; Power allocation; Matched-filter reception; Max-min; Max-product; Geometric programming; Neurala nätverk; Strömallokering; Matchad filtermottagning; Max-min; Max-produkt; Geometrisk programmering;

   Sammanfattning : This thesis considers the uplink of cell-free single input multiple output systems, in which the access points employ matched-filter reception. In this setting, our objectiveis to develop a scalable uplink power control scheme that relies only on large-scale channel gain estimates and is robust to changes in the environment. LÄS MER