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<p>Digital signal processing systems include digital filters for processing any type of signal. The digital filters are categorized as IIR and FIR filters. FIR filters are most commonly used due to their stability and linear phase property. This paper begins with a review of multiplierless FIR filter design techniques with efficient hardware and low power consumption, highlighting their benefits and drawbacks. This paper proposed a quantum-behaved particle swarm optimization (QPSO) based hardware-efficient method using different common subexpression elimination (CSE) for the design of higher-order Interpolated FIR (IFIR) filter. The optimal IFIR filter coefficients are obtained with the application of CSE algorithms using single optimization algorithm for complexity reduction. Different metaheuristic optimization techniques are utilized for comparison. The performances of designed IFIR filters are evaluated using total number of adders in the sign power of two terms (SPT), canonic signed digit (CSD) representation and CSE method. Cosine-modulated filter bank (CMFB) is also designed&#xa0;using the obtained filter coefficients to demonstrate effectiveness of the proposed approach. The CMFB performance is contrasted with state-of-the-art research using reconstruction error and aliasing error. The survey reveals that the accuracy and hardware efficiency of FIR filter design are greatly improved by combining sophisticated optimization methods like QPSO with multiplierless techniques like CSD and CSE. Although scalability and balancing accuracy with hardware constraints continue to be challenging, these methods exhibit great promise for real-time applications.</p>

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Design of Multiplierless Interpolated FIR Filter Bank Using Evolutionary Techniques: a Research Survey

  • 期刊论文

  • 发表日期：

    2025年7月14日

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  • Teena Soni,
  • V. Krishna,
  • A. Kumar,
  • Manoj Kumar Panda

摘要

Digital signal processing systems include digital filters for processing any type of signal. The digital filters are categorized as IIR and FIR filters. FIR filters are most commonly used due to their stability and linear phase property. This paper begins with a review of multiplierless FIR filter design techniques with efficient hardware and low power consumption, highlighting their benefits and drawbacks. This paper proposed a quantum-behaved particle swarm optimization (QPSO) based hardware-efficient method using different common subexpression elimination (CSE) for the design of higher-order Interpolated FIR (IFIR) filter. The optimal IFIR filter coefficients are obtained with the application of CSE algorithms using single optimization algorithm for complexity reduction. Different metaheuristic optimization techniques are utilized for comparison. The performances of designed IFIR filters are evaluated using total number of adders in the sign power of two terms (SPT), canonic signed digit (CSD) representation and CSE method. Cosine-modulated filter bank (CMFB) is also designed using the obtained filter coefficients to demonstrate effectiveness of the proposed approach. The CMFB performance is contrasted with state-of-the-art research using reconstruction error and aliasing error. The survey reveals that the accuracy and hardware efficiency of FIR filter design are greatly improved by combining sophisticated optimization methods like QPSO with multiplierless techniques like CSD and CSE. Although scalability and balancing accuracy with hardware constraints continue to be challenging, these methods exhibit great promise for real-time applications.