Bayesian compressive sensing of sparse signals with unknown clustering patterns M Shekaramiz, TK Moon, JH Gunther Entropy 21 (3), 247, 2019 | 23 | 2019 |
Hierarchical Bayesian approach for jointly-sparse solution of multiple-measurement vectors M Shekaramiz, TK Moon, JH Gunther 2014 48th Asilomar Conference on Signals, Systems and Computers, 1962-1966, 2014 | 22 | 2014 |
AMP-B-SBL: An algorithm for clustered sparse signals using approximate message passing M Shekaramiz, TK Moon, JH Gunther 2016 IEEE 7th Annual Ubiquitous Computing, Electronics & Mobile …, 2016 | 12 | 2016 |
Sparse Bayesian learning using variational Bayes inference based on a greedy criterion M Shekaramiz, TK Moon, JH Gunther 2017 51st Asilomar conference on signals, systems, and computers, 858-862, 2017 | 10 | 2017 |
On the block-sparsity of multiple-measurement vectors M Shekaramiz, TK Moon, JH Gunther 2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE …, 2015 | 10 | 2015 |
Sparse Signal Recovery Based on Compressive Sensing and Exploration Using Multiple Mobile Sensors M Shekaramiz Utah State University, 2018 | 8 | 2018 |
Drone path planning and object detection via QR codes; a surrogate case study for wind turbine inspection B Pinney, S Duncan, M Shekaramiz, MAS Masoum 2022 Intermountain Engineering, Technology and Computing (IETC), 1-6, 2022 | 7 | 2022 |
On the block-sparse solution of single measurement vectors M Shekaramiz, TK Moon, JH Gunther 2015 49th Asilomar Conference on Signals, Systems and Computers, 508-512, 2015 | 7 | 2015 |
Residual and wavelet based neural network for the fault detection of wind turbine blades LM N’diaye, A Phillips, MM AS, M Shekaramiz 2022 Intermountain Engineering, Technology and Computing (IETC), 1-5, 2022 | 6 | 2022 |
Exploration and data refinement via multiple mobile sensors based on Gaussian processes M Shekaramiz, TK Moon, JH Gunther 2017 51st Asilomar Conference on Signals, Systems, and Computers, 885-889, 2017 | 6 | 2017 |
Stability criterion for takagi-sugeno models F Sheikholeslam, M Shekaramiz 2011 Eighth International Conference on Fuzzy Systems and Knowledge …, 2011 | 6 | 2011 |
On the stability of continuous-time TS model M Shekaramiz, F Sheikholeslam 2011 Eighth International Conference on Fuzzy Systems and Knowledge …, 2011 | 6 | 2011 |
Locating and extracting wind turbine blade cracks using Haar-like features and clustering C Seibi, Z Ward, MM AS, M Shekaramiz 2022 Intermountain Engineering, Technology and Computing (IETC), 1-5, 2022 | 5 | 2022 |
Compressive sensing via variational Bayesian inference M Shekaramiz, TK Moon 2020 Intermountain Engineering, Technology and Computing (IETC), 1-6, 2020 | 5 | 2020 |
Exploration vs. data refinement via multiple mobile sensors M Shekaramiz, TK Moon, JH Gunther Entropy 21 (6), 568, 2019 | 5 | 2019 |
Loader and tester swarming drones for cellular phone network loading and field test: non-stochastic particle swarm optimization A Mirzaeinia, M Hassanalian, M Shekaramiz, M Mirzaeinia Journal of Autonomous Intelligence 2 (2), 14-24, 2019 | 5 | 2019 |
Sparse recovery via variational Bayesian inference: Comparing Bernoullis-Gaussians-inverse gamma and Gaussians-inverse gammas modeling M Shekaramiz, TK Moon, JH Gunther 2018 52nd Asilomar Conference on Signals, Systems, and Computers, 1969-1973, 2018 | 5 | 2018 |
Sparse Bayesian learning boosted by partial erroneous support knowledge M Shekaramiz, TK Moon, JH Gunther 2016 50th Asilomar Conference on Signals, Systems and Computers, 389-393, 2016 | 5 | 2016 |
Adaptive retransmission time out in flying Ad-Hoc network by LSTM machine learning: round trip time prediction A Mirzaeinia, M Mirzaeinia, M Shekaramiz, M Hassanalian AIAA Scitech 2020 Forum, 0053, 2020 | 4 | 2020 |
A note on Kriging and Gaussian processes M Shekaramiz, TK Moon, JH Gunther | 4 | 2019 |