Zobrazeno 1 - 10
of 1 467
pro vyhledávání: '"Gravdahl OF"'
Autor:
Jan Petter Neverdahl, Martin Uglem, Dagfinn Matre, Kristian Bernhard Nilsen, Knut Hagen, Gøril Bruvik Gravdahl, Trond Sand, Petter Moe Omland
Publikováno v:
The Journal of Headache and Pain, Vol 25, Iss 1, Pp 1-17 (2024)
Abstract Background Patients with migraine are vulnerable to insufficient sleep, but the impact of sleep restriction is largely unknown. In addition, the importance of sleep may be different in patients with migraine who mostly have attack onsets dur
Externí odkaz:
https://doaj.org/article/2ed08c1143c34210bc78756557975495
Autor:
Lundby, Erlend Torje Berg, Rasheed, Adil, Halvorsen, Ivar Johan, Reinhardt, Dirk, Gros, Sebastien, Gravdahl, Jan Tommy
The exploding research interest for neural networks in modeling nonlinear dynamical systems is largely explained by the networks' capacity to model complex input-output relations directly from data. However, they typically need vast training data bef
Externí odkaz:
http://arxiv.org/abs/2302.12667
Autor:
Lundby, Erlend Torje Berg, Robinsson, Haakon, Rasheed, Adil, Halvorsen, Ivar Johan, Gravdahl, Jan Tommy
Neural networks are rapidly gaining interest in nonlinear system identification due to the model's ability to capture complex input-output relations directly from data. However, despite the flexibility of the approach, there are still concerns about
Externí odkaz:
http://arxiv.org/abs/2301.00582
With the ever-increasing availability of data, there has been an explosion of interest in applying modern machine learning methods to fields such as modeling and control. However, despite the flexibility and surprising accuracy of such black-box mode
Externí odkaz:
http://arxiv.org/abs/2209.10861
The capability to adapt compliance by varying muscle stiffness is crucial for dexterous manipulation skills in humans. Incorporating compliance in robot motor control is crucial to performing real-world force interaction tasks with human-level dexter
Externí odkaz:
http://arxiv.org/abs/2209.09614
Deep neural networks have become very popular in modeling complex nonlinear processes due to their extraordinary ability to fit arbitrary nonlinear functions from data with minimal expert intervention. However, they are almost always overparameterize
Externí odkaz:
http://arxiv.org/abs/2209.05832
Autor:
Gravdahl, Mina, Aarstad, Olav A., Petersen, Agnes B., Karlsen, Stina G., Donati, Ivan, Czjzek, Mirjam, Åstrand, Ove Alexander Høgmoen, Rye, Philip D., Tøndervik, Anne, Sletta, Håvard, Aachmann, Finn L., Skjåk-Bræk, Gudmund
Publikováno v:
In Carbohydrate Polymers 1 November 2024 343
Publikováno v:
IEEE Access, Vol 12, Pp 15631-15641 (2024)
One of the most crucial steps toward achieving human-like manipulation skills in robots is to incorporate compliance into the robot controller. Compliance not only makes the robot’s behaviour safe but also makes it more energy efficient. In this di
Externí odkaz:
https://doaj.org/article/1e0d71a81c084173882f960d0a067b18