Dispersion entropy: A measure for time-series analysis M Rostaghi, H Azami IEEE Signal Processing Letters 23 (5), 610-614, 2016 | 636 | 2016 |
Refined composite multiscale dispersion entropy and its application to biomedical signals H Azami, M Rostaghi, D Abásolo, J Escudero IEEE Transactions on Biomedical Engineering 64 (12), 2872-2879, 2017 | 261 | 2017 |
An improved signal segmentation using moving average and Savitzky-Golay filter H Azami, K Mohammadi, B Bozorgtabar Scientific Research Publishing, 2012 | 187 | 2012 |
Amplitude-and fluctuation-based dispersion entropy H Azami, J Escudero Entropy 20 (3), 210, 2018 | 172 | 2018 |
Improved multiscale permutation entropy for biomedical signal analysis: Interpretation and application to electroencephalogram recordings H Azami, J Escudero Biomedical Signal Processing and Control 23, 28-41, 2016 | 167 | 2016 |
Refined multiscale fuzzy entropy based on standard deviation for biomedical signal analysis H Azami, A Fernández, J Escudero Medical & biological engineering & computing 55, 2037-2052, 2017 | 164 | 2017 |
Amplitude-aware permutation entropy: Illustration in spike detection and signal segmentation H Azami, J Escudero Computer methods and programs in biomedicine 128, 40-51, 2016 | 154 | 2016 |
Application of dispersion entropy to status characterization of rotary machines M Rostaghi, MR Ashory, H Azami Journal of Sound and Vibration 438, 291-308, 2019 | 101 | 2019 |
Measures of resting state EEG rhythms for clinical trials in Alzheimer's disease: Recommendations of an expert panel C Babiloni, X Arakaki, H Azami, K Bennys, K Blinowska, L Bonanni, ... Alzheimer's & Dementia 17 (9), 1528-1553, 2021 | 98 | 2021 |
Refined composite multivariate generalized multiscale fuzzy entropy: A tool for complexity analysis of multichannel signals H Azami, J Escudero Physica A: Statistical Mechanics and its Applications 465, 261-276, 2017 | 89 | 2017 |
Multiscale Fluctuation-based Dispersion Entropy and its Applications to Neurological Diseases H Azami, SE Arnold, S Sanei, Z Chang, G Sapiro, J Escudero, AS Gupta IEEE Access 7, 68718-68733, 2019 | 84 | 2019 |
Multivariate multiscale dispersion entropy of biomedical times series H Azami, A Fernández, J Escudero Entropy 21 (9), 913, 2019 | 70 | 2019 |
Classification of GPS satellites using improved back propagation training algorithms H Azami, MR Mosavi, S Sanei Wireless personal communications 71, 789-803, 2013 | 65 | 2013 |
Univariate and multivariate generalized multiscale entropy to characterise EEG signals in Alzheimer’s disease H Azami, D Abásolo, S Simons, J Escudero Entropy 19 (1), 31, 2017 | 62 | 2017 |
Coarse-graining approaches in univariate multiscale sample and dispersion entropy H Azami, J Escudero Entropy 20 (2), 138, 2018 | 61 | 2018 |
Two-dimensional dispersion entropy: An information-theoretic method for irregularity analysis of images H Azami, LEV da Silva, ACM Omoto, A Humeau-Heurtier Signal Processing: Image Communication 75, 178-187, 2019 | 52 | 2019 |
Fuzzy entropy metrics for the analysis of biomedical signals: Assessment and comparison H Azami, P Li, SE Arnold, J Escudero, A Humeau-Heurtier IEEE Access 7, 104833-104847, 2019 | 48 | 2019 |
An intelligent approach for variable size segmentation of non-stationary signals H Azami, H Hassanpour, J Escudero, S Sanei Journal of advanced research 6 (5), 687-698, 2015 | 47 | 2015 |
Multiscale dispersion entropy for the regional analysis of resting-state magnetoencephalogram complexity in Alzheimer's disease H Azami, E Kinney-Lang, A Ebied, A Fernández, J Escudero 2017 39th Annual International Conference of the IEEE Engineering in …, 2017 | 40 | 2017 |
Spike detection approaches for noisy neuronal data: assessment and comparison H Azami, S Sanei Neurocomputing 133, 491-506, 2014 | 40 | 2014 |