Udaya Sampath K. Perera Miriya Thanthrige

Orcid: 0000-0003-0009-9496

Affiliations:
  • Ruhr-Universität Bochum, Institute of Digital Communication Systems, Germany


According to our database1, Udaya Sampath K. Perera Miriya Thanthrige authored at least 13 papers between 2016 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2023
Resilient Sparse Array Radar with the Aid of Deep Learning.
Proceedings of the 97th IEEE Vehicular Technology Conference, 2023

2022
Low-rank plus sparse minimization and supervised learning concepts for wireless sensing based object identification
PhD thesis, 2022

Deep Unfolding of Iteratively Reweighted ADMM for Wireless RF Sensing.
Sensors, 2022

2021
Clutter Suppression for Indoor Self-Localization Systems by Iteratively Reweighted Low-Rank Plus Sparse Recovery.
Sensors, 2021

Deep Learning for DOA Estimation in MIMO Radar Systems via Emulation of Large Antenna Arrays.
IEEE Commun. Lett., 2021

A comparative Study of Low-Rank-plus-Sparse Matrix Decomposition and Machine Learning for Non-Destructive Air-Ultrasound Defect Detection.
Proceedings of the 29th European Signal Processing Conference, 2021

2020
Deep Learning for Direction of Arrival Estimation via Emulation of Large Antenna Arrays.
CoRR, 2020

Supervised learning based super-resolution DoA estimation utilizing antenna array extrapolation.
Proceedings of the 91st IEEE Vehicular Technology Conference, 2020

2019
Evaluating Forwarding Protocols in Opportunistic Networks: Trends, Advances, Challenges and Best Practices.
Future Internet, 2019

Supervised Learning Based Super Resolution DOA Estimation Utilizing Antenna Array Subsets.
CoRR, 2019

Ensemble-Based Learning in Indoor Localization: A Hybrid Approach.
Proceedings of the 90th IEEE Vehicular Technology Conference, 2019

2016
Intrusion Alert Prediction Using a Hidden Markov Model.
CoRR, 2016

Machine learning techniques for intrusion detection on public dataset.
Proceedings of the 2016 IEEE Canadian Conference on Electrical and Computer Engineering, 2016


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