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Conglomeration of Reptile Search Algorithm and Differential Evolution Algorithm for Optimal Designing of FIR Filter

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Abstract

To solve the problems of sluggish convergence at local minima, a combination of reptile search algorithms with differential evolution (CRSADE) has been developed. The conglomerated algorithm also includes a lens opposition-based learning method, which boosts population diversity and speeds up convergence. The differential evolution algorithm used in the developed CRSADE improves the exploration of the reptile search algorithm through its high ability to locate feasible regions with the best solution. This accelerates convergence by enhancing the end product of the algorithm. The proposed CRSADE helps in designing finite impulse response filters in which absolute error difference is utilized as a fitness function which is minimized by the proposed CRSADE to obtain optimal filter coefficients. To demonstrate its superiority and consistency, a comparison has been made between the developed method and other existing optimization algorithms. The developed filter satisfies the intended objective effectively with lower ripples in the pass band and higher attenuation in the stop band.

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Data Availability

Data is available on request from the authors.

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Author information

Authors and Affiliations

  1. Department of Computer Science, National Institute of Technology Delhi, New Delhi, 110 036, India

    Sumika Chauhan

  2. Precision Metrology Laboratory, Department of Mechanical Engineering, Sant Longowal Institute of Engineering and Technology, Longowal, 148 106, India

    Govind Vashishtha

  3. College of Mechanical and Electrical Engineering, Wenzhou University, Wenzhou, 325 035, China

    Anil Kumar

  4. Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, Amman, 19328, Jordan

    Laith Abualigah

  5. Faculty of Information Technology, Middle East University, Amman, 11831, Jordan

    Laith Abualigah

  6. Faculty of Information Technology, Applied Science Private University, Amman, 11931, Jordan

    Laith Abualigah

  7. School of Computer Sciences, Universiti Sains Malaysia, 11800, George Town, Pulau Pinang, Malaysia

    Laith Abualigah

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  1. Sumika Chauhan
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  2. Govind Vashishtha
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  3. Anil Kumar
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  4. Laith Abualigah
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Correspondence to Govind Vashishtha.

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Chauhan, S., Vashishtha, G., Kumar, A. et al. Conglomeration of Reptile Search Algorithm and Differential Evolution Algorithm for Optimal Designing of FIR Filter. Circuits Syst Signal Process 42, 2986–3007 (2023). https://doi.org/10.1007/s00034-022-02255-5

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