| An empirical mode decomposition-based detection and classification approach for marine mammal vocal signals KD Seger, MH Al-Badrawi, JL Miksis-Olds, NJ Kirsch, AP Lyons The Journal of the Acoustical Society of America 144 (6), 3181-3190, 2018 | 27 | 2018 |
| An EMD-based double threshold detector for spectrum sensing in cognitive radio networks MH Al-Badrawi, NJ Kirsch 2015 IEEE 82nd Vehicular Technology Conference (VTC2015-Fall), 1-5, 2015 | 12 | 2015 |
| An EMD Based Spectrum Sensing Technique for Cognitive Radio Networks MH Al-Badrawi, NJ Kirsch 2015 IEEE Vehicular Technology Conference (VTC Spring), 1-5, 2015 | 12* | 2015 |
| A de-noising scheme based on the null hypothesis of intrinsic mode functions MH Al-Badrawi, BZ Al-Jewad, WJ Smith, NJ Kirsch IEEE Signal Processing Letters 23 (7), 924-928, 2016 | 10 | 2016 |
| Intrinsic Mode Function Based Noise Power Estimation With Applications to Semiblind Spectrum Sensing Methods MH Al-Badrawi, NJ Kirsch, BZ Al-Jewad IEEE Signal Processing Letters 24 (7), 1088-1092, 2017 | 9 | 2017 |
| An Optimized De-noising Scheme based on the Null Hypothesis of Intrinsic Mode Functions JR Smith, M Al-Badrawi, NJ Kirsch IEEE Signal Processing Letters, 2019 | 6 | 2019 |
| An Intrinsic Mode Function based energy detector for spectrum sensing in cognitive radio MH Al-Badrawi, NJ Kirsch, BZ Al-Jewad International Conference on Computing, Networking and Communications (ICNC …, 2017 | 4 | 2017 |
| Statistical Properties and Applications of Empirical Mode Decomposition MH Al-Badrawi University of New Hampshire, 2017 | 3 | 2017 |
| Techniques for empirical mode decomposition (EMD)-based signal de-noising using statistical properties of intrinsic mode functions (IMFs) NJ Kirsch, MH Al-Badrawi, BZ Al-Jewad US Patent 11,257,509, 2022 | 2 | 2022 |
| An adaptive energy detection scheme using EMD for spectrum sensing MH Al-Badrawi, AM Nasr, BZ Al-Jewad, NJ Kirsch 2017 14th IEEE Annual Consumer Communications & Networking Conference (CCNC …, 2017 | 2 | 2017 |
| Noise estimation for spectrum sensing schemes MH Al-Badrawi, NJ Kirsch, BZ Al-Jewad 2016 IEEE 84th Vehicular Technology Conference (VTC-Fall), 1-2, 2016 | 2 | 2016 |
| Caller ID for Risso’s and Pacific White-sided dolphins MH Al-Badrawi, Y Liang, KD Seger, CM Foster, NJ Kirsch Scientific Reports 12 (1), 4510, 2022 | 1 | 2022 |
| Visualization, detection and classification of Risso's and Pacific white-sided dolphins using an empirical mode decomposition-based process MH Al-Badrawi, Y Liang, NJ Kirsch, KD Seger The Journal of the Acoustical Society of America 148 (4_Supplement), 2766-2766, 2020 | 1 | 2020 |
| Bearing Stake 1977 revisited: An understanding of ambient sound sources in the Indian Ocean MH Al-Badrawi, JL Miksis-Olds, DL Bradley The Journal of the Acoustical Society of America 148 (4), EL320-EL325, 2020 | 1 | 2020 |
| Variational Mode Decomposition-based Identification of Pygmy Blue Whales Song Units Y Liang, MH Al-Badrawi, KD Seger, NJ Kirsch IEEE Sensors Journal, 2024 | | 2024 |
| North Atlantic right whale calls monitoring: Signal processing meets deep learning A Durgam, Z Haider, S Aremu, M Najishabahang, M Al-Badrawi The Journal of the Acoustical Society of America 153 (3_supplement), A125-A125, 2023 | | 2023 |
| Ambient sound characterization over decadal time scales in the Atlantic Ocean MH Al-Badrawi, KD Heaney The Journal of the Acoustical Society of America 152 (4_Supplement), A290-A291, 2022 | | 2022 |
| Techniques for Empirical Mode Decomposition (EMD)-Based Noise Estimation MH Al-Badrawi, NJ Kirsch, BZ Al-Jewad US Patent App. 17/452,815, 2022 | | 2022 |
| Techniques for empirical mode decomposition (EMD)-based noise estimation MH Al-Badrawi, NJ Kirsch, BZ Al-Jewad US Patent 11,169,190, 2021 | | 2021 |
| Evaluating empirical and variational mode decomposition capabilities on Risso’s and Pacific white-sided dolphin pulsed signals in a sparse and noisy dataset KD Seger, Y Liang, MH Al-Badrawi, C Foster, NJ Kirsch The Journal of the Acoustical Society of America 150 (4_Supplement), A158-A158, 2021 | | 2021 |
Nicholas J. KirschUniversity of New HampshireVerified email at unh.edu
