A novel approach for optimal design of digital FIR filter using grasshopper optimization algorithm.

Area of Science:

• Digital Signal Processing
• Computational Intelligence
• Filter Design

Background:

• Designing digital filters requires optimizing coefficients to match ideal frequency responses.
• Swarm-based optimization algorithms are increasingly used for complex design problems.

Purpose of the Study:

• To apply the grasshopper optimization algorithm (GOA) for designing linear phase finite impulse response (FIR) filters.
• To evaluate the effectiveness of GOA in optimizing filter coefficients for various filter types (low pass, high pass, band pass, band stop).

Main Methods:

• Utilized the grasshopper optimization algorithm (GOA), a swarm-based technique modeling grasshopper foraging behavior.
• Employed an absolute error difference fitness function to minimize and obtain optimal FIR filter coefficients.
• Designed low pass, high pass, band pass, and band stop filters using the GOA.

Main Results:

• GOA-designed filters demonstrated efficient objective achievement with reduced passband ripples.
• Achieved higher stopband attenuation compared to existing algorithms.
• Showcased superior performance and consistency against cuckoo search, particle swarm optimization, and artificial bee colony algorithms.
• Required the least execution time among compared methods.

Conclusions:

• The grasshopper optimization algorithm (GOA) is a highly effective method for designing linear phase FIR filters.
• GOA offers a robust and efficient alternative for digital filter design, outperforming established optimization techniques.
• The proposed approach yields filters with improved spectral characteristics and computational efficiency.