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ORCIDJanne M. J. Huttunen
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2020 – today
- 2023
[j8]Janne M. J. Huttunen
, Dani Korpi, Mikko Honkala:
DeepTx: Deep Learning Beamforming With Channel Prediction. IEEE Trans. Wirel. Commun. 22(3): 1855-1867 (2023)- [j7]Jaakko Pihlajasalo, Dani Korpi, Mikko Honkala, Janne M. J. Huttunen, Taneli Riihonen, Jukka Talvitie, Alberto Brihuega, Mikko A. Uusitalo, Mikko Valkama:
Deep Learning OFDM Receivers for Improved Power Efficiency and Coverage. IEEE Trans. Wirel. Commun. 22(8): 5518-5535 (2023) - [c4]Dani Korpi, Mikko Honkala, Janne M. J. Huttunen:
Deep Learning-Based Pilotless Spatial Multiplexing. ACSSC 2023: 1025-1029 - [i6]Dani Korpi, Mikko Honkala, Janne M. J. Huttunen:
Deep Learning-Based Pilotless Spatial Multiplexing. CoRR abs/2312.05158 (2023) - 2022
- [i5]Dani Korpi, Mikko Honkala, Janne M. J. Huttunen, Fayçal Ait Aoudia, Jakob Hoydis:
Waveform Learning for Reduced Out-of-Band Emissions Under a Nonlinear Power Amplifier. CoRR abs/2201.05524 (2022) - [i4]Janne M. J. Huttunen, Dani Korpi, Mikko Honkala:
DeepTx: Deep Learning Beamforming with Channel Prediction. CoRR abs/2202.07998 (2022) - 2021
- [j6]Mikko Honkala, Dani Korpi, Janne M. J. Huttunen:
DeepRx: Fully Convolutional Deep Learning Receiver. IEEE Trans. Wirel. Commun. 20(6): 3925-3940 (2021) - [c3]Jaakko Pihlajasalo, Dani Korpi, Mikko Honkala, Janne M. J. Huttunen, Taneli Riihonen, Jukka Talvitie, Mikko A. Uusitalo, Mikko Valkama:
Deep Learning Based OFDM Physical-Layer Receiver for Extreme Mobility. ACSCC 2021: 395-399 - [c2]Dani Korpi, Mikko Honkala, Janne M. J. Huttunen, Vesa Starck:
DeepRx MIMO: Convolutional MIMO Detection with Learned Multiplicative Transformations. ICC 2021: 1-7 - [c1]Jaakko Pihlajasalo, Dani Korpi, Mikko Honkala, Janne M. J. Huttunen, Taneli Riihonen, Jukka Talvitie, Alberto Brihuega, Mikko A. Uusitalo, Mikko Valkama:
HybridDeepRx: Deep Learning Receiver for High-EVM Signals. PIMRC 2021: 622-627 - [i3]Jaakko Pihlajasalo, Dani Korpi, Mikko Honkala, Janne M. J. Huttunen, Taneli Riihonen, Jukka Talvitie, Alberto Brihuega, Mikko A. Uusitalo, Mikko Valkama:
HybridDeepRx: Deep Learning Receiver for High-EVM Signals. CoRR abs/2106.16079 (2021) - 2020
- [i2]Mikko Honkala, Dani Korpi, Janne M. J. Huttunen:
DeepRx: Fully Convolutional Deep Learning Receiver. CoRR abs/2005.01494 (2020) - [i1]Dani Korpi, Mikko Honkala, Janne M. J. Huttunen, Vesa Starck:
DeepRx MIMO: Convolutional MIMO Detection with Learned Multiplicative Transformations. CoRR abs/2010.16283 (2020)
2010 – 2019
- 2019
- [j5]Eeva-Sofia Haukipuro, Ville Kolehmainen, Janne M. J. Huttunen, Sebastian Remander, Janne Salo, Tuomas Takko, Le Ngu Nguyen, Stephan Sigg, Rainhard Dieter Findling:
Mobile Brainwaves: On the Interchangeability of Simple Authentication Tasks with Low-Cost, Single-Electrode EEG Devices. IEICE Trans. Commun. 102-B(4): 760-767 (2019) - [j4]Janne M. J. Huttunen, Leo Kärkkäinen, Harri Lindholm:
Pulse transit time estimation of aortic pulse wave velocity and blood pressure using machine learning and simulated training data. PLoS Comput. Biol. 15(8) (2019) - 2018
- [j3]Janne M. J. Huttunen, Jari P. Kaipio, Heikki Haario:
Approximation error approach in spatiotemporally chaotic models with application to Kuramoto-Sivashinsky equation. Comput. Stat. Data Anal. 123: 13-31 (2018) - [j2]Antti Lipponen, Janne M. J. Huttunen, Sami Romakkaniemi, Harri Kokkola, Ville Kolehmainen:
Correction of Model Reduction Errors in Simulations. SIAM J. Sci. Comput. 40(1) (2018) - 2016
- [j1]Janne M. J. Huttunen, Mikael J. Turunen, Juuso T. J. Honkanen, Juha Töyräs, Jukka S. Jurvelin:
Estimation of Systematic and Spatially Correlated Components of Random Signals from Repeated Measurements: Application to Contrast Enhanced Computer Tomography Measurements. SIAM J. Sci. Comput. 38(1) (2016)
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