ir. M.A. Coutino

1. Advances in Distributed Graph Filtering
   M. Coutino; E. Isufi; G. Leus;
   IEEE Tr. Signal Processing,
   Volume 67, Issue 9, pp. 2320-2333, May 2019. DOI: 10.1109/TSP.2019.2904925
   document

2. Sparse Antenna and Pulse Placement for Colocated MIMO Radar
   E. Tohidi; M. Coutino; S.P. Chepuri; H. Behroozi; M.M. Nayebi; G. Leus;
   IEEE Tr. Signal Processing,
   Volume 67, Issue 3, pp. 579-593, February 2019. DOI: 10.1109/TSP.2018.2881656
   document

3. Asynchronous Distributed Edge-Variant Graph Filters
   Mario Coutino; Geert Leus;
   In 2019 IEEE Data Science Workshop (DSW),
   IEEE, pp. 115--119, 2019. ISBN: 978-1-7281-0709-7. DOI: 10.1109/DSW.2019.8755577
   
   Abstract: ...

   As the size of the sensor network grows, synchronization starts to become the main bottleneck for distributed computing. As a result, efforts in several areas have been focused on the convergence analysis of asynchronous computational methods. In this work, we aim to cross-pollinate distributed graph filters with results in parallel computing to provide guarantees for asynchronous graph filtering. To alleviate the possible reduction of convergence speed due to asynchronous updates, we also show how a slight modification to the graph filter recursion, through operator splitting, can be performed to obtain faster convergence. Finally, through numerical experiments the performance of the discussed methods is illustrated.
   
   document

4. Phase-based distance determination for wireless sensor networks
   T. Kazaz; M. Coutino; G.J.M. Janssen; G.J.T. Leus; A.J. van der Veen;
   Patent, USPTO 621 81 5,1 64, March 2019.

5. Submodular Sparse Sensing for Gaussian Detection With Correlated Observations
   M. Coutino; S. P. Chepuri; G. Leus;
   IEEE Transactions on Signal Processing,
   Volume 66, Issue 15, pp. 4025-4039, August 2018. ISSN: 1053-587X. DOI: 10.1109/TSP.2018.2846220
   document

6. Subset selection for kernel-based signal reconstruction
   M. Coutino; S.P. Chepuri; G. Leus;
   In 2018 IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP),
   Calgary (Canada), IEEE, pp. 4014-4018, April 2018. ISSN: 2379-190X. DOI: 10.1109/ICASSP.2018.8461510
   document

7. Distributed Analytical Graph Identification
   S.P. Chepuri; M. Coutino; A. G. Marques; G. Leus;
   In 2018 IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP),
   Calgary (Canada), IEEE, pp. 4064-4068, April 2018. ISSN: 2379-190X. DOI: 10.1109/ICASSP.2018.8461484
   document

8. Edge-Variant Graph Filters
   G. Leus; M. Coutino; E. Isufi;
   In Graph Signal Processing Workshop (GSP18),
   Lausanne (CH), IEEE, June 2018.

9. Sparsest network support estimation: a submodular approach
   M. Coutino; S.P. Chepuri; G. Leus;
   In IEEE Data Science Workshop (DSW18),
   Lausanne (CH), IEEE, pp. 200-204, June 2018. DOI: 10.1109/DSW.2018.8439890
   document

10. Joint Ranging and Clock Synchronization for a Dense Heterogeneous IoT Networks
    T. Kazaz; M. Coutino; G. Leus; A.J. van der Veen; G. Janssen;
    In 52nd Asilomar Conference on Signals, Systems and Computers,
    Asilomar, CA, IEEE, pp. 2169-2173, November 2018. DOI: 10.1109/ACSSC.2018.8645210
    document

11. Sampling and Reconstruction of Signals on Product Graphs
    G. Ortiz-Jimenez; M. Coutino; S.P. Chepuri; G. Leus;
    In Proc. of the IEEE Global Conference on Signal and Information Processing (GlobalSIP 2018),
    Anaheim, California, USA, November 2018.

12. On the Limits of Finite-Time Distributed Consensus through Successive Local Linear Operations
    M. Coutino; E. Isufi; G. Leus;
    In 52nd Asilomar Conference on Signals, Systems and Computers,
    IEEE, November 2018.

13. Greedy alternative for room geometry estimation from acoustic echoes: a subspace-based method
    M. Coutino; M.B. Moller; J.K. Nielsen; R. Heusdens;
    In Int. Conf. Audio Speech Signal Proc. (ICASSP),
    New Orleans (USA), IEEE, pp. 366-370, March 2017. DOI: 10.1109/ICASSP.2017.7952179
    document

14. Sparse Sensing for Composite Matched Subspace Detection
    M. Coutino; S. P. Chepuri; G. Leus;
    In 2017 IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),
    Curacao, IEEE, December 2017. ISBN 978-1-5386-1250-7.

15. Near-Optimal Greedy Sensor Selection for MVDR Beamforming with Modular Budget Constraint
    M. Coutino; S.P. Chepuri; G.J.T. Leus;
    In 25th European Signal Processing Conference (EUSIPCO 2017),
    Kos (Greece), EURASIP, pp. 2035-2039, August 2017. ISBN 978-0-9928626-7-1. DOI: 10.23919/EUSIPCO.2017.8081556
    document

16. DOA Estimation and Beamforming Using Spatially Under-Sampled AVS Arrays
    K. Nambur Ramamohan; M. M. Coutino; S.P. Chepuri; D. Fernandez Comesana; G. Leus;
    In 2017 IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),
    Curacao, IEEE, December 2017. ISBN 978-1-5386-1250-7.

17. Distributed Edge-Variant Graph Filters
    M. Coutino; E. Isufi; G. Leus;
    In 2017 IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),
    Curacao, IEEE, December 2017. ISBN 978-1-5386-1250-7.

18. Direction of arrival estimation based on information geometry
    M. Coutino; R. Pribic; G. Leus;
    In Int. Conf. Audio Speech Signal Proc. (ICASSP),
    Shanghai (China), IEEE, March 2016.
    document

19. Stochastic resolution analysis of co-prime arrays in radar
    R. Pribic; M. Coutino; G. Leus;
    In IEEE Stat. Signal Proc. Workshop,
    June 2016. DOI: 10.1109/SSP.2016.7551757
    document

20. Bound on the estimation grid size for sparse reconstruction in direction of arrival estimation
    M. Coutino; R. Pribic; G. Leus;
    In IEEE Stat. Signal Proc. Workshop,
    June 2016. DOI: 10.1109/SSP.2016.7551781
    document

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