Linear Phase Filter Design using Namib Beetle and SALP Swarm Optimization Algorithm for Ripple Reduction
DOI:
https://doi.org/10.15662/IJEETR.2026.0802394Keywords:
Linear Phase Filter, Ripple Reduction, Namib Beetle Optimization, Hybrid Optimization, FIR Filter Design, Frequency Response, Signal ProcessingAbstract
Ripple reduction is a fundamental requirement in digital signal processing and power electronic applications, as excessive ripple adversely affects signal integrity, system stability, and overall performance. Linear phase filters are widely preferred in such applications because they preserve the phase characteristics of signals, ensuring distortion-free transmission. However, designing linear phase filters with minimal passband and stopband ripples while maintaining computational efficiency remains a challenging task.
This study presents an efficient linear phase filter design approach using a hybrid optimization technique that combines Namib Beetle Optimization (NBO) and the Salp Swarm Algorithm (SSA) for effective ripple reduction. The proposed method leverages the strengths of both algorithms to achieve a balanced exploration and exploitation process. NBO is inspired by the water-harvesting behavior of Namib desert beetles and is highly effective in exploring the global search space. On the other hand, SSA is based on the swarming behavior of salps in oceans and is well-suited for local search and convergence toward optimal solutions.
By integrating these two algorithms, the hybrid approach enhances the optimization process, avoiding premature convergence and improving the quality of the obtained solution. The filter coefficients are optimized to minimize both passband and stopband ripples while maintaining a sharp transition band and linear phase response.
Simulation results demonstrate that the hybrid NBO-SSA-based filter design significantly outperforms existing methods in terms of ripple suppression, computational efficiency, and robustness under varying design constraints. The optimized filter exhibits improved amplitude response, reduced distortion, and enhanced stability, making it highly suitable for real-time signal processing applications.
Overall, the proposed hybrid optimization framework provides an effective and reliable solution for linear phase filter design with superior ripple reduction performance. It has potential applications in communication systems, biomedical signal processing, image processing, and power electronics where high precision and low distortion are critical.
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