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B., Iliadis, L., Maglogiannis, I. (eds.) ICANN 2018. LNCS, vol. 11140, pp. 511–520.
Springer, Cham (2018). https://doi.org/10.1007/978-3-030-01421-6_49
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using Consensus matching pursuit. In: 1st International Conference on Advanced
Technologies for Signal and Image Processing (ATSIP). IEEE press, Sousse (2014)
13. Wang, S., et al.: Ripple classification helps to localize the seizure-onset zone in neocortical
epilepsy. J. Epilepsia. 54, 370–376 (2013)
Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing,
adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons
license and indicate if changes were made.
The images or other third party material in this chapter are included in the chapter’s Creative
Commons license, unless indicated otherwise in a credit line to the material. If material is not
included in the chapter’s Creative Commons license and your intended use is not permitted by
statutory regulation or exceeds the permitted use, you will need to obtain permission directly
from the copyright holder.
Evaluation of Stationary Wavelet Transforms in Reconstruction
363
ripples. J. Neurosc. Meth. 213, 236–249 (2012)
6. Jmail, N., et al.: Integration of stationary wavelet transform on a dynamic partial
reconfiguration for recognition of pre-ictal gamma oscillations. Heliyon 4(2), e00530 (2018)
7. Tang, Z.P., Xu, S.L., Dai, X.Y., Hu, X.J., Liao, X.L., Cai, J.: S-wave tracing technique to
investigate the damage and failure behavior of brittle materials subjected to shock loading.
Int. J. Impact Eng 31, 1172–1191 (2005)
8. Wang, X.H., Istepanian, R.S.H., Song, Y.H.: Microarray image de-noising using stationary
wavelet transform. In: 4th International IEEE EMBS Special Topic Conference on Information
Technology Applications in Biomedicine, pp. 15–18. IEEE press, Birmingham (2003)
9. Abdennour, N., Hadriche, A., Frikha, T., Jmail, N.: Extraction and localization of noncontaminated alpha and gamma oscillations from EEG signal using finite impulse response,
stationary wavelet transform, and custom FIR. In: Kůrková, V., Manolopoulos, Y., Hammer,
B., Iliadis, L., Maglogiannis, I. (eds.) ICANN 2018. LNCS, vol. 11140, pp. 511–520.
Springer, Cham (2018). https://doi.org/10.1007/978-3-030-01421-6_49
10. Wang, S., et al.: Scalable social sensing of interdependent phenomena. In: 14th International
Conference on Information Processing in Sensor Networks, pp. 202–213 (2015)
11. Frikha, T., et al.: Adaptive architecture for medical application case study: evoked Potential
detection using matching poursuit consensus. In: 15th International Conference on
Intelligent Systems Design and Applications (ISDA). IEEE press, Morocco (2015)
12. Hadriche A., et al.: The detection of Evoked Potential with variable latency and multiple trial
using Consensus matching pursuit. In: 1st International Conference on Advanced
Technologies for Signal and Image Processing (ATSIP). IEEE press, Sousse (2014)
13. Wang, S., et al.: Ripple classification helps to localize the seizure-onset zone in neocortical
epilepsy. J. Epilepsia. 54, 370–376 (2013)
Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing,
adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons
license and indicate if changes were made.
The images or other third party material in this chapter are included in the chapter’s Creative
Commons license, unless indicated otherwise in a credit line to the material. If material is not
included in the chapter’s Creative Commons license and your intended use is not permitted by
statutory regulation or exceeds the permitted use, you will need to obtain permission directly
from the copyright holder.
Evaluation of Stationary Wavelet Transforms in Reconstruction
363