The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.
Automatic recognition of alertness level from EEG by using neural network and wavelet coefficients
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Citations
Cites
Neural Networks: A Comprehensive Foundation
Haykin, S. (1998) · Cited by 30,070
Daubechies, I. (1992) · doi:10.1137/1.9781611970104 · Cited by 15,979
Daubechies, I., & Heil, C. (1992) · Computers in Physics · doi:10.1063/1.4823127 · Cited by 15,631
Artificial neural networks: fundamentals, computing, design, and application
Basheer, I. A., & Hajmeer, M. (2000) · Journal of Microbiological Methods · doi:10.1016/s0167-7012(00)00201-3 · Cited by 3,231
Fundamentals of neural networks: architectures, algorithms, and applications
Fausett, L. V. (1994) · CERN Document Server (European Organization for Nuclear Research) · Cited by 3,025
Wavelets and signal processing
Rioul, O., & Vetterli, M. (1991) · IEEE Signal Processing Magazine · doi:10.1109/79.91217 · Cited by 2,786
Analysis of EEG records in an epileptic patient using wavelet transform
Adeli, H., Zhou, Z., & Dadmehr, N. (2003) · Journal of Neuroscience Methods · doi:10.1016/s0165-0270(02)00340-0 · Cited by 1,154
Estimating alertness from the EEG power spectrum
Jung, T.-P., Makeig, S., Stensmo, M., & Sejnowski, T. J. (1997) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.553713 · Cited by 480
Neural classification of lung sounds using wavelet coefficients
Kandaswamy, A., Kumar, C. S., Ramanathan, R. P., Jayaraman, S., & Malmurugan, N. (2004) · Computers in Biology and Medicine · doi:10.1016/s0010-4825(03)00092-1 · Cited by 370
A normative study of the maintenance of wakefulness test (MWT)
Doghramji, K., Mitler, M. M., Sangal, R. B., Shapiro, C., Taylor, S., Walsleben, J., Belisle, C., Erman, M. K., Hayduk, R., Hosn, R., et al. (1997) · Electroencephalography and Clinical Neurophysiology · doi:10.1016/s0013-4694(97)00010-2 · Cited by 331
Cited by
EEG signal classification using wavelet feature extraction and a mixture of expert model.
SUBASI, A. (2007) · Expert Systems with Applications · doi:10.1016/j.eswa.2006.02.005 · Cited by 1,182
Self-citationUsing EEG spectral components to assess algorithms for detecting fatigue
Jap, B. T., Lal, S., Fischer, P., & Bekiaris, E. (2009) · Expert Systems with Applications · doi:10.1016/j.eswa.2007.12.043 · Cited by 729
EEG Based Emotion Recognition: A Tutorial and Review
Li, X., Zhang, Y., Tiwari, P., Song, D., Hu, B., Yang, M., Zhao, Z., Kumar, N., & Marttinen, P. (2023) · ACM Computing Surveys · doi:10.1145/3524499 · Cited by 508
EEG Signal Classification Using Wavelet Feature Extraction and Neural Networks
Jahankhani, P., Kodogiannis, V., & Revett, K. (2006) · IEEE John Vincent Atanasoff 2006 International Symposium on Modern Computing (JVA'06) · doi:10.1109/jva.2006.17 · Cited by 313
Emotion recognition from multi-channel EEG data through Convolutional Recurrent Neural Network
Li, X., Song, D., Zhang, P., Yu, G., Hou, Y., & Hu, B. (2016) · 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm.2016.7822545 · Cited by 283
Metadata
- Authors
- SUBASI, A.
- Venue
- Expert Systems with Applications
- Publisher
- Elsevier BV
- Published
- 2005-05
- Volume
- 28
- Issue
- 4
- Pages
- 701-711
- ISSN
- 0957-4174 (ISSN-L)
- OpenAlex
- W1969675008
- Cited by
- 289
- References
- 22
- FWCI
- 5.14
- Type
- journal article
- Language
- en
- Open access
- closed
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- SUBASI, A. (2005). Automatic recognition of alertness level from EEG by using neural network and wavelet coefficients. Expert Systems with Applications. https://doi.org/10.1016/j.eswa.2004.12.027
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
