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A Hybrid Modified Sine Cosine Algorithm Using Inverse Filtering and Clipping Methods for Low Autocorrelation Binary Sequences

Siti Julia Rosli1,2, Hasliza A Rahim1,2,*, Khairul Najmy Abdul Rani1,2, Ruzelita Ngadiran2,3, Wan Azani Mustafa3,4, Muzammil Jusoh1,2, Mohd Najib Mohd Yasin1,2, Thennarasan Sabapathy1,2, Mohamedfareq Abdulmalek5, Wan Suryani Firuz Wan Ariffin2, Ahmed Alkhayyat6

1 Advanced Communication Engineering, Centre of Excellence (ACE), Universiti Malaysia Perlis (UniMAP), 01000 Kangar, Perlis, Malaysia
2 Faculty of Electronic Engineering Technology, Universiti Malaysia Perlis (UniMAP), 02600 Arau, Perlis, Malaysia
3 Advanced Computing (AdvCOMP), Centre of Excellence, Universiti Malaysia Perlis (UniMAP), 02600 Arau, Perlis, Malaysia
4 Faculty of Electrical Engineering Technology, Universiti Malaysia Perlis (UniMAP), 02600 Arau, Perlis, Malaysia
5 Faculty of Engineering and Information Science, University of Wollongong in Dubai, Dubai 20183, United Arab Emirates
6 Department of Computer Technical Engineering, College of Technical Engineering, the Islamic University, 54001 Najaf, Iraq

* Corresponding Author: Hasliza A Rahim. Email: email

Computers, Materials & Continua 2022, 71(2), 3533-3556. https://doi.org/10.32604/cmc.2022.021719

A retraction of this article was approved in:

Retraction: A Hybrid Modified Sine CosineAlgorithm Using Inverse Filtering andClipping Methods forLow AutocorrelationBinary Sequences
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Abstract

The essential purpose of radar is to detect a target of interest and provide information concerning the target's location, motion, size, and other parameters. The knowledge about the pulse trains’ properties shows that a class of signals is mainly well suited to digital processing of increasing practical importance. A low autocorrelation binary sequence (LABS) is a complex combinatorial problem. The main problems of LABS are low Merit Factor (MF) and shorter length sequences. Besides, the maximum possible MF equals 12.3248 as infinity length is unable to be achieved. Therefore, this study implemented two techniques to propose a new metaheuristic algorithm based on Hybrid Modified Sine Cosine Algorithm with Cuckoo Search Algorithm (HMSCACSA) using Inverse Filtering (IF) and clipping method to achieve better results. The proposed algorithms, LABS-IF and HMSCACSA-IF, achieved better results with two large MFs equal to 12.12 and 12.6678 for lengths 231 and 237, respectively, where the optimal solutions belong to the skew-symmetric sequences. The MF outperformed up to 24.335% and 2.708% against the state-of-the-art LABS heuristic algorithm, xLastovka, and Golay, respectively. These results indicated that the proposed algorithm's simulation had quality solutions in terms of fast convergence curve with better optimal means, and standard deviation.

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APA Style
Rosli, S.J., Rahim, H.A., Rani, K.N.A., Ngadiran, R., Mustafa, W.A. et al. (2022). A hybrid modified sine cosine algorithm using inverse filtering and clipping methods for low autocorrelation binary sequences. Computers, Materials & Continua, 71(2), 3533-3556. https://doi.org/10.32604/cmc.2022.021719
Vancouver Style
Rosli SJ, Rahim HA, Rani KNA, Ngadiran R, Mustafa WA, Jusoh M, et al. A hybrid modified sine cosine algorithm using inverse filtering and clipping methods for low autocorrelation binary sequences. Comput Mater Contin. 2022;71(2):3533-3556 https://doi.org/10.32604/cmc.2022.021719
IEEE Style
S.J. Rosli et al., “A Hybrid Modified Sine Cosine Algorithm Using Inverse Filtering and Clipping Methods for Low Autocorrelation Binary Sequences,” Comput. Mater. Contin., vol. 71, no. 2, pp. 3533-3556, 2022. https://doi.org/10.32604/cmc.2022.021719



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