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  5. A hybrid modified sine cosine algorithm using inverse filtering and clipping methods for low autocorrelation binary sequences
 
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A hybrid modified sine cosine algorithm using inverse filtering and clipping methods for low autocorrelation binary sequences

Journal
Computers, Materials and Continua
ISSN
15462218
Date Issued
2022-01-01
Author(s)
Rosli S.J.
Universiti Malaysia Perlis
Hasliza A Rahim @ Samsuddin
Universiti Malaysia Perlis
Khairul Najmy Abdul Rani
Universiti Malaysia Perlis
Ruzelita Ngadiran
Universiti Malaysia Perlis
Wan Azani Wan Mustafa
Universiti Malaysia Perlis
Abdulmalek M.
University ofWollongong, Dubai
Mohd Najib Mohd Yasin
Universiti Malaysia Perlis
Muzammil Jusoh
Universiti Malaysia Perlis
Thennarasan Sabapathy
Universiti Malaysia Perlis
Wan Nur Suryani Firuz Wan Ariffin
Universiti Malaysia Perlis
Alkhayyat A.
College of Technical Engineering, the Islamic University
DOI
10.32604/cmc.2022.021719
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 mainlywell 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 maximumpossibleMF 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. TheMFoutperformed 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.
Subjects
  • Antenna and propagati...

  • Autocorrelation

  • Combinatorial optimiz...

  • Cuckoo search algorit...

  • Merit factor

  • Radar system

  • Sine cosine algorithm...

  • Skew-symmetric sequen...

  • Wearable antenna

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Nov 19, 2024
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