References on the Hilbert Vibration Decomposition

  • M. J. Singh, L. N. Sharma and S. Dandapat, “Time-Frequency Based Detection of Mitral Regurgitation Using Seismocardiogram Signal,” 2023 21st International Conference on ICT and Knowledge Engineering (ICT&KE), Bangkok, Thailand, 2023, pp. 1-5, doi: 10.1109/ICTKE58576.2023.10401827.
  • P. -L. Cheng and C. -L. Yang, “Heart Rate Detection With Hilbert Vibration Decomposition in Random Body Movements Based on FMCW Radars,” in IEEE Microwave and Wireless Technology Letters, vol. 33, no. 6, pp. 935-938, June 2023, doi: 10.1109/LMWT.2023.3268347.
  • Qinghua Liu, Junyi Cao, Ying Zhang, Zhenyang Zhao, Gaëtan Kerschen, Xingjian Jing, Interpretable sparse identification of a bistable nonlinear energy sink, Mechanical Systems and Signal Processing, Volume 193, 2023, 110254, ISSN 0888-3270, https://doi.org/10.1016/j.ymssp.2023.110254.
  • Qinghua Liu et al, 2023 J. Phys. D: Appl. Phys. 56 044005, DOI 10.1088/1361-6463/acaab8
  • Can Chen, Qihang Li, Weimin Wang, Torsional vibration feature extraction method from lateral vibrations based on decomposed forward and backward whirl motions, Journal of Sound and Vibration, 2022, 117491, ISSN 0022-460X, https://doi.org/10.1016/j.jsv.2022.117491
  • Liu, Q., Zhang, Y., Hou, Z. et al. Optimal Hilbert transform parameter identification of bistable structures. Nonlinear Dyn (2022). https://doi.org/10.1007/s11071-022-08120-z
  • Swarup Nandi, Shivam Parashar, Madhusudhan Mishra, & Swanirbhar Majumder. (2022). Heart Sound Segregation from Breath Sound Using Hilbert Variational Decomposition. Journal of Coastal Life Medicine, 10(3), 310–324, https://jclmm.com/index.php/journal/article/view/194
  • M. J. Singh, L. N. Sharma and S. Dandapat, “Hilbert Vibration Decomposition of Seismocardiogram for HR and HRV Estimation,” 2022 IEEE International Conference on Signal Processing and Communications (SPCOM), 2022, pp. 1-5, doi: 10.1109/SPCOM55316.2022.9840838.
  • Ali Yener Mutlu, Detection of epileptic dysfunctions in EEG signals using Hilbert vibration decomposition, Biomedical Signal Processing and Control, Volume 40, 2018, Pages 33-40, ISSN 1746-8094, https://doi.org/10.1016/j.bspc.2017.08.023.
  • Ren, X. Modal Parameter Identification of Nonlinear Systems Based on Hilbert Vibration Decomposition. Iran J Sci Technol Trans Civ Eng (2022). https://doi.org/10.1007/s40996-022-00914-w
  • Yue Zhao, Xiaoyu Zhao, Liang Tong, Adaptive Noise Removal for Biological Raman Spectra with Low SNR, Vibrational Spectroscopy, 2022, 103441, ISSN 0924-2031, https://doi.org/10.1016/j.vibspec.2022.103441.
  • Vesala, G.T., Ghali, V.S., Rama Sastry, D.V.A. et al. Thermal Wave Mode Decomposition for Defect Detection in Non-Stationary Thermal Wave Imaging. MAPAN (2022). https://doi.org/10.1007/s12647-022-00587-w
  • Qinghua Liu, Junyi Cao, Zehao Hou, Ying Zhang, and Xingjian Jing, Identification of Stiffness Force in Nonlinear Piezoelectric Structures Based on Hilbert Transform, X. Jing et al. (Eds.): ICANDVC 2021, LNEE 799, pp. 584–596, 2022, https://link.springer.com/content/pdf/10.1007%2F978-981-16-5912-6_43.pdf
  • A. Shankar, S. Dandapat and S. Barma, “Classification of Epileptic Seizure From EEG Signal Based on Hilbert Vibration Decomposition and Deep Learning,” 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021, pp. 2802-2805, doi: 10.1109/EMBC46164.2021.9631081.
  • Shibo Wang, Bin Tang, Estimating quadratic and cubic stiffness nonlinearity of a nonlinear vibration absorber with geometric imperfections, Measurement, 2021, 110005, ISSN 0263-2241, https://doi.org/10.1016/j.measurement.2021.110005.
  • Pritam Khan, Yasin Khan, Sudhir Kumar, Mohammad S. Khan, Amir H. Gandomi, HVD-LSTM based Recognition of Epileptic Seizures and Normal Human Activity, Computers in Biology and Medicine, 2021, 104684, ISSN 0010-4825, https://doi.org/10.1016/j.compbiomed.2021.104684.
  • Yingzhi Xia, Hui Li, Zhezhe Fan, Jiyong Xiao, “Modal Parameter Identification Based on Hilbert Vibration Decomposition in Vibration Stability of Bridge Structures”, Advances in Civil Engineering, vol. 2021, Article ID 6688686, 9 pages, 2021. https://doi.org/10.1155/2021/6688686
  • Li, C., Cao, Y. Modal Parameter Identification Based on an Enhanced Hilbert Vibration Decomposition. Iran J Sci Technol Trans Civ Eng (2021). https://doi.org/10.1007/s40996-021-00705-9
  • Xiaoyu Zhao, Ming Xu, Wei Zhang, Guoyi Liu, Liang Tong, Identification of zinc pollution in rice plants based on two characteristic variables, Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, Volume 261, 2021, 120043, ISSN 1386-1425, https://doi.org/10.1016/j.saa.2021.120043.
  • Ihor Javorskyj, Roman Yuzefovych, Ivan Matsko, Pavlo Kurapov, Hilbert transform of a periodically non-stationary random signal: Low-frequency modulation, Digital Signal Processing, 2021, 103113, ISSN 1051-2004, https://doi.org/10.1016/j.dsp.2021.103113.
  • Civera, M.; Surace, C. A Comparative Analysis of Signal Decomposition Techniques for Structural Health Monitoring on an Experimental Benchmark. Sensors 2021, 21, 1825. https://doi.org/10.3390/s21051825
  • Raja Krishnamoorthy,Siva Shankar. S,Pogu Vignan, REAL TIME WIRELESS ECG SIGNAL-BASED HEART DISEASE PREDICTION SYSTEM USING HVD, JOURNAL OF MECHANICS OF CONTINUA AND MATHEMATICAL SCIENCES, Vol – 15 No -3, March 2020, https://doi.org/10.26782/jmcms.2020.03.00015
  • Syuhri, S.N.H.; Zare-Behtash, H.; Cammarano, A. Investigating the Influence of Fluid-Structure Interactions on Nonlinear System Identification. Vibration 2020, 3, 521-544. https://doi.org/10.3390/vibration3040032
  • Seyed Bahram Beheshti Aval, Vahid Ahmadian, Mohammad Maldar, et al.,
    Damage detection of structures using signal processing and artificial neural networks
    Advances in Structural Engineering, Volume: 23 issue: 5, 2020, page(s): 884-897, https://doi.org/10.1177/1369433219886079
  • Mingjie Zhang, Fuyou Xu, Zhanbiao Zhang, Xuyong Ying, Energy budget analysis and engineering modeling of post-flutter limit cycle oscillation of a bridge deck, Journal of Wind Engineering and Industrial Aerodynamics, Volume 188, 2019, Pages 410-420, ISSN 0167-6105,
    https://doi.org/10.1016/j.jweia.2019.03.010
  • G. Asbjornsson, I. Erdem, M. Evertsson, Application of the Hilbert transform for diagnostic and control in crushing, Minerals Engineering, Volume 147, 2020, 106086, ISSN 0892-6875, https://doi.org/10.1016/j.mineng.2019.106086.
  • Barkin Buyukcakir, Furkan Elmaz, Ali Yener Mutlu, Hilbert Vibration Decomposition-based epileptic seizure prediction with neural network, Computers in Biology and Medicine, Volume 119, 2020, 103665, ISSN 0010-4825, https://doi.org/10.1016/j.compbiomed.2020.103665. (http://www.sciencedirect.com/science/article/pii/S0010482520300585)
  • HAIXIA LI1, YONGFENG REN, GUOJUN ZHANG, RENXIN WANG,JIANGONG CUI, AND WENDONG ZHANG, Detection and Classification of Abnormitiesof First Heart Sound Using EmpiricalWavelet Transform, Digital Object Identifier, ctober 7, 2019, 10.1109/ACCESS.2019.2943705
  • Ilker Erdem, Gauti Asbjornsson, Henrik Kihlman, Feedforward control for oscillatory signal tracking using Hilbert transform, European Journal of Control,
    Volume 50, 2019, Pages 41-50, ISSN 0947-3580, https://doi.org/10.1016/j.ejcon.2019.06.002.
  • Wei Yumiao, Zhang Zhili, Chang Zhengjun, Zhao Junyang, Li Xiangyang. Simulation Analyses of a Method for Extracting Dynamic Parameters from Forced Vibration Responses[J]. Journal of System Simulation, 2019, 31(4): 618-623. https://doi: 10.16182/j.issn1004731x.joss.19-0093
  • Shiliang Lu and Juwei Zhang, “Quantitative Nondestructive Testing of Wire Ropes Based on Features Fusion of Magnetic Image and Infrared Image,” Shock and Vibration, vol. 2019, Article ID 2041401, 15 pages, 2019.https://doi.org/10.1155/2019/2041401.
  • Xiaoxun Zhu, Jianhong Zhao, Dongnan Hou, and Zhonghe Han, An SDP Characteristic Information Fusion-Based CNN Vibration Fault Diagnosis Method, Shock and Vibration, Hindawi, Volume 2019, Article ID 3926963, 14 pages, https://doi.org/10.1155/2019/3926963
  • Harikesh, A. Basu, M. P. Abegaonkar, and S. K. Koul, “Through the Wall Respiration Rate Detection of Multiple Human Subjects
    Using Hilbert Vibrational Decomposition,” Progress In Electromagnetics Research M, Vol. 80, 83-91, 2019.doi:10.2528/PIERM19020103.
  • Li Yuefeng, Zhou Xingliang, Rolling bearing fault diagnosis based on HVD algorithm and sample entropy, Journal of Computational Methods in Sciences and Engineering, vol. Pre-press, no. Pre-press, pp. 1-10, 2019, DOI: 10.3233/JCM-191048
  • Sharma, H., Extraction of respiration from PPG signals using Hilbert vibration decomposition, 2019, ACM International Conference Proceeding Series, pp. 48-52
  • Buyukcakir, Barktn; Mutlu, Ali Yener, Comparison of Hilbert Vibration Decomposition with Empirical Mode Decomposition for Classifying Epileptic Seizures, ISSN: 1058-6393; ISBN: 1-5386-9219-8 , 1-5386-9218-X; DOI:10.1109/ACSSC.2018.8645274 2018 52nd Asilomar Conference on Signals, Systems, and Computers , 2018, Vol.2018-October, p.357-362.
  • Tian-Chen Yuan, Jian Yang and Li-Qun Chen, Nonparametric Identification of Nonlinear Piezoelectric Mechanical Systems,
    J. Appl. Mech 85(11), 111008 (Aug 24, 2018) (13 pages)
    Paper No: JAM-18-1141; doi: 10.1115/1.4040949
  • Marco Tarabini, Diego Scaccabarozzi, Uncertainty-based combination of signal processing techniques for the identification of rotor imbalance, Measurement, Volume 114, 2018, Pages 409-416, ISSN 0263-2241, https://doi.org/10.1016/j.measurement.2017.10.006.
  • Pawel Lajmert, Rafal Rusinek and Bogdan Kruszynski, Chatter identification in milling of Inconel 625 based on recurrence plot technique and Hilbert vibration decomposition, MATEC Web of Conferences, 148, 09003 (2018), ICoEV 2017, https://doi.org/10.1051/matecconf/201814809003
  • Y. Long, Y. Guo and L. Zhao, “Planet gear fault diagnosis based on HVD and envelope time-domain synchronous average,” 2018 Chinese Control And Decision Conference (CCDC), Shenyang, 2018, pp. 4052-4057.
    doi: 10.1109/CCDC.2018.8407827, URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8407827&isnumber=8407034
  • Ondra V Sever I Schwingshackl C, A method for non-parametric identification of non-linear vibration systems with asymmetric restoring forces from a resonant decay response, Mechanical Systems and Signal Processing, 2019 vol: 114 pp: 239-258, DOI: 10.1016/J.YMSSP.2018.05.0
  • Urvashi Prakash Shukla and Satyasai Jagannath Nanda, Denoising hyperspectral images using Hilbert vibration decomposition with cluster validation, Source: IET Image Processing, DOI: 10.1049/iet-ipr.2017.1234.
  • Madhusudhan Mishra, Sanmitra Banerjee, Dennis C. Thomas, Detection of Third Heart Sound Using Variational Mode Decomposition,
    IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, VOL. 67, NO. 7, JULY 2018.
  • Solomon Davis, Izhak Bucher, Automatic vibration mode selection and excitation; combining modal filtering with autoresonance, Mechanical Systems and Signal Processing, Volume 101, 2018, Pages 140-155, ISSN 0888-3270, https://doi.org/10.1016/j.ymssp.2017.08.009.
  • Sharma H, Sharma KK, ECG-derived respiration based on iterated Hilbert transform and Hilbert vibration decomposition,
    Australas Phys Eng Sci Med. 2018 Jun;41(2):429-443. doi: 10.1007/s13246-018-0640-0. Epub 2018 Apr 17.
  • Rusinek Rafal, Marcin Szymanski, and Pawel Lajmert, Vibration of middle ear with shape memory prosthesis – Experimental and numerical study, AIP Conference Proceedings 1922, 120013 (2018); doi: 10.1063/1.5019128
  • Mohammed Assam OUALI, Mouna GHANAI, Kheireddine CHAFAA, Upper envelope detection of ECG signals for baseline wander correction: a pilot study, Turk J Elec Eng & Comp Sci, (2018) 26: 803 – 816, doi:10.3906/elk-1705-165
  • Ismail, S., Siddiqi, I. & Akram, U.,Localization and classification of heart beats in phonocardiography signals —a comprehensive review, EURASIP J. Adv. Signal Process. (2018) 2018: 26. https://doi.org/10.1186/s13634-018-0545-9,
  • Cooper, S. B., D. DiMaio, and D. J. Ewins. 2018. “Integration of System Identification and Finite Element Modelling of Nonlinear Vibrating Structures.” Mechanical Systems and Signal Processing 102: 401-430. doi:10.1016/j.ymssp.2017.09.031
  • Xiaoxun Zhu; Yiming Yuan; Pei Zhou; Bochao Xu; Zhonghe Han, An improved Hilbert vibration decomposition method for analysis of rotor fault signals, J Braz. Soc. Mech. Sci. Eng. (2017) 39: 4921. https://doi.org/10.1007/s40430-017-0886-6
  • Tiejun Cao, A New Method of Voltage Flicker Detection for Hilbert Vibration Decomposition, Indonesian Journal of Electrical Engineering and Computer Science, Vol. 7, No. 1, July 2017, pp. 43-51, DOI: 10.11591/ijeecs.v7.i1.pp43-51
  • Ali Yener Mutlu, Detection of epileptic dysfunctions in EEG signals using Hilbert vibration decomposition,
    In Biomedical Signal Processing and Control, Volume 40, 2018, Pages 33-40, ISSN 1746-8094, https://doi.org/10.1016/j.bspc.2017.08.023.
  • Tianchen Yuan, JianYang, Li-Qun Chen, Experimental identification of hardening and softening nonlinearity in circular laminated plates, International Journal of Non-Linear Mechanics, Volume 95, October 2017, pp. 296-306,
    https://doi.org/10.1016/j.ijnonlinmec.2017.07.007
  • Li-Qun Chen, and Tianchen Yuan, Nonparametric Identification of a Nonlinear Piezoelectric Vibration Energy Harvester,
    ENOC 2017, June25 – 30, 2017, Budapest, Hungary
  • Yi Qin, Yongfang Mao, Baoping Tang, Multicomponent decomposition by wavelet modulus maxima and synchronous detection,
    Mechanical Systems and Signal Processing, Volume 91, 2017, Pages 57-80, ISSN 0888-3270, http://dx.doi.org/10.1016/j.ymssp.2017.01.002.
  • Faizuddin Musafere, Kefu Liu, Ayan Sadhu, IDENTIFICATION OF INSTANTANEOUS FREQUENCIES OF AN AXIALLY-MOVING CANTILEVER BEAM USING THE HILBERT VIBRATION DECOMPOSITION, The 23rd International Congress on Sound and Vibration, ICSV23, Athens (Greece), 10-14 July 2016.
  • Yi Qin, Qingliang Zhang, Yongfang Mao, Baoping Tang, Vibration component separation by iteratively using stochastic resonance with different frequency-scale ratios, Measurement, Volume 94, 2016, Pages 538-553, ISSN 0263-2241, http://dx.doi.org/10.1016/j.measurement.2016.09.006.
  • N. Saxena and K.K. Sharma, Hilbert vibration decomposition based image fusion, Electronics Letters, Volume 52, Issue 19, 15 September 2016, p. 1605 – 1607
  • Nidhi Saxena ; Kamalesh K. Sharma, Pansharpening approach using Hilbert vibration decomposition, IET Image Processing, Volume 11, Issue 12, 2017, Page(s): 1152 – 1162, DOI: 10.1049/iet-ipr.2017.0133
  • Yi Qin, Baoping Tang, Yongfang Mao, Adaptive signal decomposition based on wavelet ridge and its application, Signal Processing, Volume 120, March 2016, pp. 480–494, doi:10.1016/j.sigpro.2015.09.032
  • Jian Tang, Zhiwei Wu, Zhuo Liu, Ball Mill Shell Vibration Signal Analysis Strategy Based on DEM-FEM Method and Multi-Component Signal Adaptive Decomposition Technique, International Forum on Management, Education and Information Technology Application, Atlantis Press, 2016/01, pp. 2352-5398, https://doi.org/10.2991/ifmeita-16.2016.55
  • Michael Feldman, Simon Braun, Nonlinear vibrating system identification via Hilbert decomposition, Mechanical Systems and Signal Processing (2017), pp. 65-96 DOI information: 10.1016/j.ymssp.2016.03.015
  • Michael Feldman, Yaron Zimmerman, Michael Gissin and Izhak Bucher, Identification and modeling of contact dynamics of precise direct drive stages, Journal of Dynamic Systems, Measurement, and Control, 2016;138(7):071001-071001-10. doi:10.1115/1.4033017.
  • Feng Zhipeng,Qin Sifeng. Planetary Gearbox Fault Diagnosis Based on Hilbert Vibration Decomposition and Higher Order Differential Energy Operator[J]. JOURNAL OF VIBRATION AND SHOCK, 2016, 35(5): 47-54.
  • Waclaw Gawedzki, Bartosz Serzysko, The application of HVD transformation for paraseismic signals analysis in the time domain, Przeglad Elektrotechniczny(Electrical Review), No/VOL: 08/2015, pp. 7-10
  • Marco Tarabini, Andrea Gironacci, Roberto Panzeri, Diego Scaccabarozzi, Signal processing techniques for the identification of wheels’ imbalance in presence of disturbances, Proceedings of the 9th IFToMM International Conference on Rotor Dynamics, Mechanisms and Machine Science Volume 21, 2015, pp 475-483
  • Shovan Barma, Bo-Wei Chen, Hung-Ming Wang, Hung-Jui Wang, Jhing-Fa Wang,
    Second Heart Sound (S2) Decomposition by Hilbert Vibration Decomposition (HVD) for Affective Signal Modeling and Learning, Advances in Web-Based Learning – ICWL 2013 Workshops Advances in Web-Based Learning – ICWL 2013 Workshops, Lecture Notes in Computer Science Volume 8390, 2015, pp 223-233
  • Jian Tang; Yi Kan; Zhuo Liu; Tianyou Chai, Modelling load parameters of ball mill using frequency spectral features based on Hilbert vibration decomposition, Information and Automation (ICIA), 2014 IEEE International Conference on, Haoilar, pp. 1055 – 1060, DOI:
    10.1109/ICInfA.2014.6932805
  • Sharma, H., Sharma, K.K., Baseline wander removal of ECG signals using Hilbert vibration decomposition, Electronics Letters (Impact Factor: 1.07). 01/2015; 51(6):447-449. DOI: 10.1049/el.2014.4076
  • JJ Ramos, JI Reyes, E Barocio, An improved Hilbert Vibration Decomposition method for analysis of low frequency oscillations,
    (PES T&D-LA), 2014 IEEE PES, 2014
  • M. Bertha, J.C. Golinval, Identification of a Time-varying Beam Using Hilbert Vibration Decomposition, IMAC XXXII, Orlando, Florida USA, February 3-6, 2014
  • P. Li, Y. Zhao, Application of Hilbert Vibration Decomposition in Analysis of non-stationary Oscillation Events in CSG, CIGRE, the Council on Large Electric Systems, Lisbon Symposium, Lisboa, Portugal – April 22-24, 2013
  • M. Feldman, Mapping nonlinear forces with congruent vibration functions, MSSP, 37(2013), pp. 315-337.
  • Y. Huang, C.J. Yan, Q. Xu, On the difference between empirical mode decomposition and Hilbert vibration decomposition for earthquake motion records, 15th World Conference on Earthquake Engineering (15WCEE), Lisbon, Portugal, 24-28, 2012
  • M. Feldman, Nonparametric identification of asymmetric nonlinear vibration systems with the Hilbert transform, Journal of Sound and Vibration. 331 (2012), pp. 3386-339.
  • Nadav Cohen, Izhak Bucher and Michael Feldman, Slow-fast response decomposition of a bi-stable energy harvester, Mechanical Systems and Signal Processing, (31), 2012, pp. 29-39 .
  • Niklas Klugel, PRACTICAL EMPIRICAL MODE DECOMPOSITION FOR AUDIO SYNTHESIS. Proc. of the 15th Int. Conference on Digital Audio Effects (DAFx-12), York, UK , September 17-21, 2012
  • Shen Yue,Liu Guohai,Liu Hui, Transient and Steady Power Harmonic Analysis Based on Hilbert Vibration Decomposition Method, Journal of Data Acquisition and Processing, 2011, 26(1), pp. 117-122
  • S. Braun, M. Feldman, Decomposition of non-stationary signals into varying time scales: Some aspects of the EMD and HVD methods, Mechanical Systems and Signal Processing, (October 2011), 25 (7), pp. 2608-2630.
  • M. Feldman, Hilbert Transform Applications in Mechanical Vibration, Wiley, 2011,
  • Peng Li, Yong Zhang, Hongtao Liu, Yong Zhao, Zhaobin Du, ANALYSIS OF NON-STATIONARY AND NONLINEAR LOW-FREQUENCY OSCILLATION OF A REALISTIC BULK POWER SYSTEM IN A TIME-FREQUENCY PERSPECTIVE, 2010,
  • Starosvetsky, Y.; Gendelman, O. V., Interaction of nonlinear energy sink with a two degrees of freedom linear system: Internal resonance, Journal of Sound and Vibration, 2010, Volume 329, Issue 10, p. 1836-1852.
  • LIU Hui,LIU Guo-hai,SHEN Yue, Novel Method for Non-integer Harmonics Measurement Using Hilbert Vibration Decomposition, High Voltage Engineering» 2009-07.
  • Liu Hui,Liu Guohai,Shen Yue, Novel method for detection of voltage flicker based on Hilbert vibration decomposition, Chinese Journal of Scientific Instrument, 2009-09
  • M. Feldman. Theoretical analysis and comparison of the Hilbert transform decomposition methods. Mechanical Systems and Signal
    Processing, 2008, Vol 22/3 pp. 509-519.
  • O. V. Gendelman, Y. Starosvetsky and M. Feldman. Attractors of harmonically forced linear oscillator with attached nonlinear energy
    sink I: Description of response regimes. Nonlinear Dynamics, V. 51/1-2 , 2008, pp. 31-46.
  • Feldman M. Identification of weakly nonlinearities in multiple coupled oscillators.
    Journal of Sound and Vibration. 2007, Vol.303, pp. 353-370.
  • Feldman M. Considering High Harmonics for Identification of Nonlinear Systems by Hilbert Transform. Mechanical Systems and Signal
    Processing, 2007, Vol 21/2, pp. 943-958.
  • Feldman M. Time-Varying Vibration Decomposition and Analysis Based on the Hilbert Transform. Journal of Sound and Vibration. 2006, Vol 295/3-5 pp. 518-530.