L1-Norm and LMS Based Digital FIR Filters Design Using Evolutionary Algorithms

• Published in: Journal of electrical engineering & technology Vol. 19; no. 1; pp. 753 - 762
• Main Author: Rajasekhar, K.
• Format: Journal Article
• Language: English
• Published: Singapore Springer Nature Singapore 01.01.2024; Springer Nature B.V; 대한전기학회
• Subjects: Electrical Engineering; Electrical Machines and Networks; Electronics and Microelectronics; Engineering; Instrumentation; Original Article; Power Electronics; 전기공학; Grasshopper optimization; Cuckoo search; Digital FIR filters; Parks–McClellan method; Fitness function
• ISSN: 1975-0102; 2093-7423
• DOI: 10.1007/s42835-023-01589-7

The suggested work in this paper involves the construction of digital filters by utilizing optimization algorithms to compute optimum filter coefficients in such a way that the designed filter's magnitude response is identical to the ideal one. The proposed work takes a nature-inspired approach to optimizing the design of 20th order linear phase finite impulse response (FIR) based low pass, high pass and band pass filters. This approach involves the cuckoo search optimization algorithm (CSA) and Grasshopper optimization algorithms (GOA) by minimizing the least mean square error function and L 1 -norm based ones. These GOA and CSA are used to find the best possible values for the filter coefficients. The bench mark algorithm to design the FIR filter as Parks–McClellan approach and other recently published optimization algorithms are used to prove the superiority of proposed designs. Compared with PM method, real coded genetic algorithm, Cat swarm, Particle swarm optimization and some hybrid optimization based ones, the proposed design results have been outperform. Moreover, the proposed FIR filters give the best outcome, effectively meeting the target with decreased pass band ripples and higher attenuation in the stop band with a least execution time.