https://oldena.lpnu.ua/handle/ntb/52530| Title: | Analysis of EEG using Multilayer Neural Network with Multi-Valued Neurons |
| Authors: | Aizenberg, Igor Khaliq, Zain |
| Affiliation: | Manhattan College Riverdale |
| Bibliographic description (Ukraine): | Aizenberg I. Analysis of EEG using Multilayer Neural Network with Multi-Valued Neurons / Igor Aizenberg, Zain Khaliq // Data stream mining and processing : proceedings of the IEEE second international conference, 21-25 August 2018, Lviv. — Львів : Lviv Politechnic Publishing House, 2018. — P. 392–396. — (Hybrid Systems of Computational Intelligence). |
| Bibliographic description (International): | Aizenberg I. Analysis of EEG using Multilayer Neural Network with Multi-Valued Neurons / Igor Aizenberg, Zain Khaliq // Data stream mining and processing : proceedings of the IEEE second international conference, 21-25 August 2018, Lviv. — Lviv Politechnic Publishing House, 2018. — P. 392–396. — (Hybrid Systems of Computational Intelligence). |
| Is part of: | Data stream mining and processing : proceedings of the IEEE second international conference, 2018 |
| Conference/Event: | IEEE second international conference "Data stream mining and processing" |
| Issue Date: | 28-Feb-2018 |
| Publisher: | Lviv Politechnic Publishing House |
| Place of the edition/event: | Львів |
| Temporal Coverage: | 21-25 August 2018, Lviv |
| Keywords: | Complex-Valued Neural Networks Multi-Valued Neuron Multilayer Neural Network with Multi-Valued Neurons MLMVN EEG Fourier transform |
| Number of pages: | 5 |
| Page range: | 392-396 |
| Start page: | 392 |
| End page: | 396 |
| Abstract: | There is a wealth of analysis techniques that can be used in analyzing data of such a nature as EEG (Electroencephalogram), yet there are still many more ways and possibilities of analysis techniques to consider in order to produce a method that far exceeds the capabilities of the prevalent method. Since a multilayer neural network with multi-valued neurons (MLMVN) was successfully used earlier to decode EEG signals in a brain/computer interface (BCI) by analysis of their Fourier transform, it seemed very attractive to use it as a tool for EEG analysis. This work aims to further investigate how a complex-valued machine learning tool can be used to analyze EEG in the frequency domain. Our goal was to check how Fourier transform and complex wavelet transform of EEG can be analyzed using MLMVN in order to diagnose epilepsy, its remission or absence. We worked with a commonly used benchmark data set of epilepsy-related EEGs. The analysis of the transformed data was performed to determine a set of relevant statistical characteristics of DTCWT and Fourier transform components, which were then used as inputs of the MLMVN. The obtained results show a very high efficiency of the proposed approach. |
| URI: | https://ena.lpnu.ua/handle/ntb/52530 |
| ISBN: | © Національний університет „Львівська політехніка“, 2018 © Національний університет „Львівська політехніка“, 2018 |
| Copyright owner: | © Національний університет “Львівська політехніка”, 2018 |
| URL for reference material: | http://www.uniklu.ac.at/tewi/downloads/masterthesis_TrampitschStefan_Final_Version.pdf |
| References (Ukraine): | [1] A. Hirose, Complex-Valued Neural Networks, 2nd Edn.. Springer, Berlin, Heidelberg, 2012. [2] D. Mandic and V. Su Lee Goh, Complex Valued Nonlinear Adaptive Filters: Noncircularity, Widely Linear and Neural Models. John Wiley & Sons, 2009. [3] I. Aizenberg, I., Complex-Valued Neural Networks with MultiValued Neurons. Berlin: Springer-Verlag Publishers, 2011. [4] Y.Nakano, and A.Hirose, “Improvement of Plastic Landmine Visualization Performance by use of ring-CSOM and FrequencyDomain Local Correlation,” IEICE Transactions on Electronics, vol. E92-C, iss. 1, pp. 102-108, Jan. 2009. [5] S. L. Goh, M. Chen, D. H. Popovic, K. Aihara, D. Obradovic and D. P. Mandic, "Complex Valued Forecasting of Wind Profile,"Renewable Energy, vol. 31 , pp. 1733-1750, Sep. 2006. [6] A. Handayani, A.B.Suksmono, T.L.R.Mengko, and A.Hirose, “Blood Vessel Segmentation in Complex-Valued Magnetic Resonance Images with Snake Active Contour Model,” International Journal of E-Health and Medical Communications, vol. 1, iss. 1, pp. 41-52, Jan. 2010. [7] I. Aizenberg, L. Sheremetov, L. Villa-Vargas, and J. MartinezMuñoz, "Multilayer Neural Network with Multi-Valued Neurons in Time Series Forecasting of Oil Production," Neurcomputing, vol. 175, part B, pp. 980-989, Jan. 2016. [8] N.V.Manyakov, I. Aizenberg, N. Chumerin, and M. Van Hulle, “Phase-Coded Brain-Computer Interface Based on MLMVN”, book chapter in Complex-Valued Neural Networks: Advances and Applications (A. Hirose – Ed.), Wiley, 2012, pp. 185-208. [9] I. Aizenberg, C. Moraga, and D. Paliy, "A Feedforward Neural Network based on Multi-Valued Neurons", In Computational Intelligence, Theory and Applications. Advances in Soft Computing , XIV, (B. Reusch - Ed.), Springer, Berlin, Heidelberg, New York, pp. 599-612, 2005. [10] I. Aizenberg, and C. Moraga, “Multilayer Feedforward Neural Network based on Multi-Valued Neurons (MLMVN) and a backpropagation learning algorithm,” Soft Computing, 11, iss. 2, pp. 169-183, Jan. 2007. [11] N. N. Aizenberg, Yu. L. Ivaskiv, D. A. Pospelov, and G.F. Hudiakov, "Multivalued Threshold Functions. Synthesis of Multivalued Threshold Elements," Cybernetics and Systems Analysis, vol. 9, no. 1, pp. 61-77, January 1973. [12] N.N. Aizenberg and I.N. Aizenberg, "CNN Based on Multi-Valued Neuron as a Model of Associative Memory for Gray-Scale Images," Proceedings of the Second IEEE International Workshop on Cellular Neural Networks and their Applications, Munich, pp.36-41, October 14-16, 1992. [13] I. Aizenberg, D. Paliy, J. Zurada, and J. Astola, "Blur Identification by Multilayer Neural Network based on Multi-Valued Neurons", IEEE Transactions on Neural Networks, vol. 19, no. 5, pp. 883-898, May 2008. [14] O. Fink, E. Zio, and U. Weidmann, “Predicting Component Reliability and Level of Degradation with Complex-Valued Neural Networks,” Reliability Engineering & System Safety, vol. 121, pp. 198–206, 2014. [15] I. Aizenberg, A. Luchetta and S. Manetti, “A modified learning algorithm for the multilayer neural network with multi-valued neurons based on the complex QR decomposition,” Soft Computing, vol. 16, iss. 4, pp. 563-575, Apr. 2012. [16] I. Aizenberg, “MLMVN with Soft Margins Learning,” IEEE Transactions on Neural Networks and Learning Systems, vol. 25, no. 9, pp. 1632-1644, September 2014. [17] I. Aizenberg, A. Luchetta, S. Manetti., and C. Piccirilli., “System Identification using FRA and a modified MLMVN with Arbitrary Complex-Valued Inputs,” Proceedings of the 2016 IEEE International Joint Conference on Neural Networks (IJCNN 2016), Vancouver, pp. 4404-4411, July, 2016. [18] E. Aizenberg and I. Aizenberg, “Batch LLS-based Learning Algorithm for MLMVN with Soft Margins,” IEEE Symposium Series of Computational Intelligence (SSCI-2014), pp. 48-55, December, 2014. [19] R. Caton, "The electric currents of brain", British Medical Journal, vol. 2, pp. 278, 1875. [20] H. Berger, "Über das Elektroenkephalogramm des Menschen", Arch Psychiatr Nervenkr, vol. 87, pp. 527-570, 1929. [21] E. D. Adrian, and B. H. C. Matthews, “The Berger rhythm: potential changes from the occipital lobes in man,” Brain: A Journal of Neurology, vol. 57, pp.355-385, 1934. [22] M. Peker, B. Sen, and D. Delen, “A Novel Method for Automated Diagnosis of Epilepsy Using Complex-Valued Classifiers,” IEEE Journal of Biomedical and Health Informatics vol. 20, no. 1, pp. 108–118, January 2016. [23] B. Sen, M. Peker, F.V. Celebi and A. Cavusoglu, “A comparative study on classification of sleep stage based on EEG signals using feature selection and classification algorithms,” Journal of Medical Systems, vol. 38, no. 18, 2014. doi: 10.1007/s10916-014-0018-0, [24] I. W.Selesnick, R. G.Baraniuk, and N. G.Kingsbury, "The Dual-Tree Complex Wavelet Transform",IEEE Signal Processing Magazine,Vol. 22, No 6, pp. 123–151, December 2005. [25] R. G. Andrzejak, G. Widman, K. Lehnertz, C. Rieke, P. David and C. E. Elger, “The epileptic process as nonlinear deterministic dynamics in a stochastic environment: an evaluation on mesial temporal lobe epilepsy,” Epilepsy Research, vol. 44, pp. 129-140, 2001. [26] S. Trampitsch, “Complex-Valued Data Estimation”, Master Thesis, Alpen-Adria-Universität Klagenfurt, Fakultät für Technische Wissenschaften, Austria, 2013, available online at http://www.uniklu.ac.at/tewi/downloads/masterthesis_TrampitschStefan_Final_Version.pdf [27] T. Adili, P. Schreier, and L.L. Scharf. “Complex-valued signal processing, The proper way to deal with impropriety,” IEEE Transactions on Signal Processing, vol. 59, no. 11, pp. 5101-5125, November 2011. [28] S. M. Kay. Statistical Signal Processing: Estimation Theory, volume 1. Prentice Hall PTR, 2010. [29] P. J. Schreier and L. L. Scharf. “Second-order analysis of improper complexrandom vectors and processes,” IEEE Transactions on Signal Processing, vol.51, no. 3, pp.s 714-725, March 2003. [30] I. Aizenberg, “Hebbian and Error-Correction Learning for ComplexValued Neurons,” Soft Computing, vol. 17, no. 2, pp. 265-273, Feb. 2013. [31] I. Aizenberg, N. Aizenberg, C. Butakov, and E. Farberov, “Image Recognition on the Neural Network based on Multi-Valued Neurons,” Proceedings of the 15th International Conference on Pattern Recognition, Barcelona, Spain, IEEE Computer Society Press, vol. 2. pp. 993-996, September 3-8, 2000. |
| References (International): | [1] A. Hirose, Complex-Valued Neural Networks, 2nd Edn.. Springer, Berlin, Heidelberg, 2012. [2] D. Mandic and V. Su Lee Goh, Complex Valued Nonlinear Adaptive Filters: Noncircularity, Widely Linear and Neural Models. John Wiley & Sons, 2009. [3] I. Aizenberg, I., Complex-Valued Neural Networks with MultiValued Neurons. Berlin: Springer-Verlag Publishers, 2011. [4] Y.Nakano, and A.Hirose, "Improvement of Plastic Landmine Visualization Performance by use of ring-CSOM and FrequencyDomain Local Correlation," IEICE Transactions on Electronics, vol. E92-C, iss. 1, pp. 102-108, Jan. 2009. [5] S. L. Goh, M. Chen, D. H. Popovic, K. Aihara, D. Obradovic and D. P. Mandic, "Complex Valued Forecasting of Wind Profile,"Renewable Energy, vol. 31 , pp. 1733-1750, Sep. 2006. [6] A. Handayani, A.B.Suksmono, T.L.R.Mengko, and A.Hirose, "Blood Vessel Segmentation in Complex-Valued Magnetic Resonance Images with Snake Active Contour Model," International Journal of E-Health and Medical Communications, vol. 1, iss. 1, pp. 41-52, Jan. 2010. [7] I. Aizenberg, L. Sheremetov, L. Villa-Vargas, and J. MartinezMuñoz, "Multilayer Neural Network with Multi-Valued Neurons in Time Series Forecasting of Oil Production," Neurcomputing, vol. 175, part B, pp. 980-989, Jan. 2016. [8] N.V.Manyakov, I. Aizenberg, N. Chumerin, and M. Van Hulle, "Phase-Coded Brain-Computer Interface Based on MLMVN", book chapter in Complex-Valued Neural Networks: Advances and Applications (A. Hirose – Ed.), Wiley, 2012, pp. 185-208. [9] I. Aizenberg, C. Moraga, and D. Paliy, "A Feedforward Neural Network based on Multi-Valued Neurons", In Computational Intelligence, Theory and Applications. Advances in Soft Computing , XIV, (B. Reusch - Ed.), Springer, Berlin, Heidelberg, New York, pp. 599-612, 2005. [10] I. Aizenberg, and C. Moraga, "Multilayer Feedforward Neural Network based on Multi-Valued Neurons (MLMVN) and a backpropagation learning algorithm," Soft Computing, 11, iss. 2, pp. 169-183, Jan. 2007. [11] N. N. Aizenberg, Yu. L. Ivaskiv, D. A. Pospelov, and G.F. Hudiakov, "Multivalued Threshold Functions. Synthesis of Multivalued Threshold Elements," Cybernetics and Systems Analysis, vol. 9, no. 1, pp. 61-77, January 1973. [12] N.N. Aizenberg and I.N. Aizenberg, "CNN Based on Multi-Valued Neuron as a Model of Associative Memory for Gray-Scale Images," Proceedings of the Second IEEE International Workshop on Cellular Neural Networks and their Applications, Munich, pp.36-41, October 14-16, 1992. [13] I. Aizenberg, D. Paliy, J. Zurada, and J. Astola, "Blur Identification by Multilayer Neural Network based on Multi-Valued Neurons", IEEE Transactions on Neural Networks, vol. 19, no. 5, pp. 883-898, May 2008. [14] O. Fink, E. Zio, and U. Weidmann, "Predicting Component Reliability and Level of Degradation with Complex-Valued Neural Networks," Reliability Engineering & System Safety, vol. 121, pp. 198–206, 2014. [15] I. Aizenberg, A. Luchetta and S. Manetti, "A modified learning algorithm for the multilayer neural network with multi-valued neurons based on the complex QR decomposition," Soft Computing, vol. 16, iss. 4, pp. 563-575, Apr. 2012. [16] I. Aizenberg, "MLMVN with Soft Margins Learning," IEEE Transactions on Neural Networks and Learning Systems, vol. 25, no. 9, pp. 1632-1644, September 2014. [17] I. Aizenberg, A. Luchetta, S. Manetti., and C. Piccirilli., "System Identification using FRA and a modified MLMVN with Arbitrary Complex-Valued Inputs," Proceedings of the 2016 IEEE International Joint Conference on Neural Networks (IJCNN 2016), Vancouver, pp. 4404-4411, July, 2016. [18] E. Aizenberg and I. Aizenberg, "Batch LLS-based Learning Algorithm for MLMVN with Soft Margins," IEEE Symposium Series of Computational Intelligence (SSCI-2014), pp. 48-55, December, 2014. [19] R. Caton, "The electric currents of brain", British Medical Journal, vol. 2, pp. 278, 1875. [20] H. Berger, "Über das Elektroenkephalogramm des Menschen", Arch Psychiatr Nervenkr, vol. 87, pp. 527-570, 1929. [21] E. D. Adrian, and B. H. C. Matthews, "The Berger rhythm: potential changes from the occipital lobes in man," Brain: A Journal of Neurology, vol. 57, pp.355-385, 1934. [22] M. Peker, B. Sen, and D. Delen, "A Novel Method for Automated Diagnosis of Epilepsy Using Complex-Valued Classifiers," IEEE Journal of Biomedical and Health Informatics vol. 20, no. 1, pp. 108–118, January 2016. [23] B. Sen, M. Peker, F.V. Celebi and A. Cavusoglu, "A comparative study on classification of sleep stage based on EEG signals using feature selection and classification algorithms," Journal of Medical Systems, vol. 38, no. 18, 2014. doi: 10.1007/s10916-014-0018-0, [24] I. W.Selesnick, R. G.Baraniuk, and N. G.Kingsbury, "The Dual-Tree Complex Wavelet Transform",IEEE Signal Processing Magazine,Vol. 22, No 6, pp. 123–151, December 2005. [25] R. G. Andrzejak, G. Widman, K. Lehnertz, C. Rieke, P. David and C. E. Elger, "The epileptic process as nonlinear deterministic dynamics in a stochastic environment: an evaluation on mesial temporal lobe epilepsy," Epilepsy Research, vol. 44, pp. 129-140, 2001. [26] S. Trampitsch, "Complex-Valued Data Estimation", Master Thesis, Alpen-Adria-Universität Klagenfurt, Fakultät für Technische Wissenschaften, Austria, 2013, available online at http://www.uniklu.ac.at/tewi/downloads/masterthesis_TrampitschStefan_Final_Version.pdf [27] T. Adili, P. Schreier, and L.L. Scharf. "Complex-valued signal processing, The proper way to deal with impropriety," IEEE Transactions on Signal Processing, vol. 59, no. 11, pp. 5101-5125, November 2011. [28] S. M. Kay. Statistical Signal Processing: Estimation Theory, volume 1. Prentice Hall PTR, 2010. [29] P. J. Schreier and L. L. Scharf. "Second-order analysis of improper complexrandom vectors and processes," IEEE Transactions on Signal Processing, vol.51, no. 3, pp.s 714-725, March 2003. [30] I. Aizenberg, "Hebbian and Error-Correction Learning for ComplexValued Neurons," Soft Computing, vol. 17, no. 2, pp. 265-273, Feb. 2013. [31] I. Aizenberg, N. Aizenberg, C. Butakov, and E. Farberov, "Image Recognition on the Neural Network based on Multi-Valued Neurons," Proceedings of the 15th International Conference on Pattern Recognition, Barcelona, Spain, IEEE Computer Society Press, vol. 2. pp. 993-996, September 3-8, 2000. |
| Content type: | Conference Abstract |
| Appears in Collections: | Data stream mining and processing : proceedings of the IEEE second international conference |
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| 2018_Aizenberg_I-Analysis_of_EEG_using_392-396.pdf | 197.67 kB | Adobe PDF | View/Open | |
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