Two‐dimensional FIR filters model order reduction and frequency transformation: Maximum error invariance

Bouhamla, Lakhdar; Adamou‐Mitiche, Amel Baha Houda; Mitiche, Lahcène

doi:10.1002/jnm.2692

Cited by 3 publications

(1 citation statement)

References 16 publications

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“…) hN . The transfer function can be expressed as(Song et al 2020;Bouhamla et al 2020) He  and ()  are the magnitude response and the phase response, respectively.If the ideal frequency response for the FIR digital filter is | ( of the square error between the amplitude of the designed filter | (…”

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confidence: 99%

FIR digital filter design based on improved artificial bee colony algorithm

Lian

Tian

2022

Soft Comput

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The traditional swarm intelligence optimization algorithm is prone to fall into local optimal solutions in finite impulse response (FIR) digital filter design, and has slow convergence speed. In order to optimize the design of FIR filter, a FIR digital filter design method based on improved bee colony (ABC) algorithm is proposed．This improved ABC algorithm can adaptively adjust the step size of the selected neighborhood of nectar source location. At the same time, the information of the global optimal solution is used to guide the search of candidate solution, which improves the global search ability of the algorithm. The improved ABC algorithm can balance the conflict between local search ability and global search ability, so it can achieve better optimization effect.The time and space complexity of the algorithm is analyzed in detail. Then, the improved ABC algorithm is used to design three typical FIR digital filters, namely low-pass, band-pass and band-stop filter. The performance of the designed filter is tested by simulation experiments. The experimental results show that compared with other state-of-the-art optimization algorithms, the proposed FIR filter design method has achieved better effect and performance. Meanwhile, the proposed design method has shorter optimization time. The superiority of the proposed method is verified.

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mentioning

confidence: 99%

FIR digital filter design based on improved artificial bee colony algorithm

Lian

Tian

2022

Soft Comput

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Projection Approach for Interval Systems Approximation: An Extension to MIMO Systems

Zerrougui

Adamou‐Mitiche

Mitiche

2022

IEEE Trans. Circuits Syst. II

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FIR Digital Filter Design Based on Improved Artificial Bee Colony Algorithm

Lian

Tian

2022

Preprint

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The traditional swarm intelligence optimization algorithm is prone to fall into local optimal solutions in finite impulse response (FIR) digital filter design, and has slow convergence speed. In order to optimize the design of FIR filter, a FIR digital filter design method based on improved bee colony (ABC) algorithm is proposed. This improved ABC algorithm can adaptively adjust the step size of the selected neighborhood of nectar source location. At the same time, the information of the global optimal solution is used to guide the search of candidate solution, which improves the global search ability of the algorithm. The improved ABC algorithm can balance the conflict between local search ability and global search ability, so it can achieve better optimization effect. The time and space complexity of the algorithm is analyzed in detail. Then, the improved ABC algorithm is used to design three typical FIR digital filters, namely low-pass, band-pass and band-stop filter. The performance of the designed filter is tested by simulation experiments. The experimental results show that compared with other state-of-the-art optimization algorithms, the proposed FIR filter design method has achieved better effect and performance. Meanwhile, the proposed design method has shorter optimization time. The superiority of the proposed method is verified.

show abstract

Two‐dimensional FIR filters model order reduction and frequency transformation: Maximum error invariance

Cited by 3 publications

References 16 publications

FIR digital filter design based on improved artificial bee colony algorithm

FIR digital filter design based on improved artificial bee colony algorithm

Projection Approach for Interval Systems Approximation: An Extension to MIMO Systems

FIR Digital Filter Design Based on Improved Artificial Bee Colony Algorithm

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