Asian Journal of Information Technology

Year: 2020
Volume: 19
Issue: 1
Page No. 1 - 11

RETRACTED ARTICLE: Optimizing Classification of Spread Spectrum Signals Based on Features Extraction

Authors : Haidy S. Fouad, Hend A. Elsayed and Shawkat K. Girgis

References

Amraoui, A., B. Benmammar, F. Krief and F.T. Bendimerad, 2012. Intelligent wireless communication system using cognitive radio. Intl. J. Distrib. Parallel Syst., 3: 91-104.
CrossRef  |  Direct Link  |  

Chandrashekar, G. and F. Sahin, 2014. A survey on feature selection methods. Comput. Electr. Eng., 40: 16-28.
CrossRef  |  Direct Link  |  

Cheng, Z. and Z. Lu, 2018. A novel efficient feature dimensionality reduction method and its application in engineering. Complexity, Vol. 2018, 10.1155/2018/2879640

Clausi, D.A., 2002. An analysis of co-occurrence texture statistics as a function of grey level quantization. Can. J. Remote Sens., 28: 45-62.
CrossRef  |  

Du, L. and Y.D. Shen, 2015. Unsupervised feature selection with adaptive structure learning. Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD’15), August 10-13, 2015, Sydney, Australian, pp: 209-218.

Fouad, H.S., H.A. Elsayed and S.K. Guirguis, 2019. Direct sequence and frequency hopping signals classification based on co-occurrence matrix and clustering techniques. J. Comp. Sci., 15: 78-91.
CrossRef  |  Direct Link  |  

Guo, J., Y. Quo, X. Kong and R. He, 2017. Unsupervised feature selection with ordinal locality. Proceedings of the 2017 IEEE International Conference on Multimedia and Expo (ICME’17), July 10-14, 2017, IEEE, Hong Kong, China, pp: 1213-1218.

Hamed, H.A., A.K. Abdullah and S. Al-Waisawy, 2018. Frequency hopping spread spectrum recognition based on discrete fourier transform and skewness and kurtosis. Int. J. Appl. Eng. Res., 13: 7081-7085.
Direct Link  |  

Haralick, R.M., K. Shanmugam and I.H. Dinstein, 1973. Textural features for image classification. IEEE Trans. Syst. Man Cybern., SMC-3: 610-621.
CrossRef  |  Direct Link  |  

Hasan, M., J.M. Thakur and P. Podder, 2016. Design and implementation of FHSS and DSSS for secure data transmission. Int. J. Signal Process. Syst., 4: 144-149.
CrossRef  |  Direct Link  |  

Jaskowiak, P.A. and R.J. Campello, 2015. A cluster based hybrid feature selection approach. Proceedings of the 2015 Brazilian Conference on Intelligent Systems (BRACIS’15), November 4-7, 2015, IEEE, Natal, Brazil, pp: 43-48.

Jayaweera, S., 2015. Signal Classification in Wideband Cognitive Radios. In: Signal Processing for Cognitive Radios, Jayaweera, S. (Ed.). Wiley, New Jersey, USA., ISBN: 9781118824931, pp: 429-471.

Jovic, A., K. Brkic and N. Bogunovic, 2015. A review of feature selection methods with applications. Proceedings of the 2015 38th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO’15), May 25-29, 2015, IEEE, Opatija, Croatia, pp: 1200-1205.

Krishnaveni N. and V. Radha, 2019. Feature selection algorithms for data mining classification: A survey. Indian J. Sci. Technol., Vol. 12, No. 6. 10.17485/ijst/2019/v12i6/139581

Kumbhar, P. and M. Mali, 2016. A survey on feature selection techniques and classification algorithms for efficient text classification. Int. J. Sci. Res., 5: 1267-1275.
Direct Link  |  

Li, J., K. Cheng, S. Wang, F. Morstatter, R.P. Trevino, J. Tang and H. Liu, 2017. Feature selection: A data perspective. ACM Comput. Surv. (CSUR.), Vol. 50,

Liu, C., W. Wang, Q. Zhao, X. Shen and M. Konan, 2017. A new feature selection method based on a validity index of feature subset. Pattern Recognit. Lett., 92: 1-8.
CrossRef  |  Direct Link  |  

Mafarja, M.M. and S. Mirjalili, 2017. Hybrid whale optimization algorithm with simulated annealing for feature selection. Neurocomputing, 260: 302-312.
CrossRef  |  Direct Link  |  

Mohamed, R., M.M. Yusof and N. Wahidi, 2018. A comparative study of feature selection techniques for bat algorithm in various applications. MATEC Web Conf., Vol. 150,

Nakamura, R.Y.M., L.A.M. Pereira, K.A. Costa, D. Rodrigues and J.P. Papa, 2012. BBA: A binary bat algorithm for feature selection. Proceedings of the 25th SIBGRAPI Conference on Graphics, Patterns and Images, August 22-25, 2012, Ouro Preto, pp: 291-297.

Normandin, M.E., S.D. Mohanty and T.S. Weerathunga, 2018. Particle swarm optimization based search for gravitational waves from compact binary coalescences: Performance improvements. Phys. Rev. D., Vol. 98, 10.1103/PhysRevD.98.044029

Pratiwi, M., Alexander, J. Harefa and S. Nanda, 2015. Mammograms classification using gray-level co-occurrence matrix and radial basis function neural network. Procedia Comput. Sci., 59: 83-91.
CrossRef  |  Direct Link  |  

Rajalakshmi and S. Jayanthi, 2017. Feature selection using wrapper method for writer identification of Tamil handwritten documents. Int. J. Comput. Technol. Appl., 8: 666-671.
Direct Link  |  

Roffo, G., 2017. Ranking to learn and learning to rank: On the role of ranking in pattern recognition applications. Ph.D. Thesis, Department of Computer Science, University of Verona (Università degli Studi di Verona), Verona, Italy.

Sanaullah, M., 2013. A review of higher order statistics and spectra in communication systems. Global J. Sci. Front. Res. Phys. Space Sci., 13: 31-50.
Direct Link  |  

Sen, B., M. Peker, A. Cavuşoglu and F.V. Celebi, 2014. A comparative study on classification of sleep stage based on EEG signals using feature selection and classification algorithms. J. Med. Syst., Vol. 38, 10.1007/s10916-014-0018-0

Soh, L.K. and C. Tsatsoulis, 1999. Texture analysis of SAR sea ice imagery using gray level co-occurrence matrices. IEEE Trans. Geosci. Remote Sens., 37: 780-795.
CrossRef  |  

Suarez-Alvarez, M.M., D.T. Pham, M.Y. Prostov and Y.I. Prostov, 2012. Statistical approach to normalization of feature vectors and clustering of mixed datasets. Proc. R. Soc. A: Math. Phys. Eng. Sci., 468: 2630-2651.
CrossRef  |  Direct Link  |  

Torrieri, D., 2005. Principles of Spread-Spectrum Communication Systems. Springer, Boston, USA.

Vanaja, S. and K.R. Kumar, 2014. Analysis of feature selection algorithms on classification: A survey. Int. J. Comput. Appl., 96: 29-35.
CrossRef  |  Direct Link  |  

Wei, X., 2007. Gray level run length matrix toolbox v1.0, software. Beijing Institute of Technology Aeronautics Astronautics Engineering Experiment Teaching Center, Beijing, China.

Zhang, X., J. Cui, W. Wang and C. Lin, 2017. A study for texture feature extraction of high-resolution satellite images based on a direction measure and gray level co-occurrence matrix fusion algorithm. Sensors, Vol. 17, 10.3390/s17071474

Design and power by Medwell Web Development Team. © Medwell Publishing 2024 All Rights Reserved