Design of Optimal FIR Filters Using Integrated Optimization Technique
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Design of Optimal FIR Filters Using Integrated Optimization Technique Teena Mittal1 Received: 20 February 2020 / Revised: 10 November 2020 / Accepted: 13 November 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract The aim of the research work is to optimally design a finite impulse response (FIR) filter. For this purpose, an integrated optimization technique has been proposed. The proposed optimization technique integrates the Moth flame optimization (MFO) technique and Powell’s pattern search (PPS) technique in a coherent manner to maintain a fine balance between exploration and exploitation capabilities of the search technique. During the search process, the best performing MFO particle is transferred to the PPS method to avoid any possible stagnation. Initially, the proposed optimization technique has been tested on five standard test functions and then it is applied to design optimal FIR low-pass, high-pass, band-pass and band-stop filters. The performance of the proposed optimization technique is compared with other state of art optimization techniques and also with the results reported in the literature. The proposed optimization technique yields high-quality solution with minimal computational efforts. Further, student t test is applied to test the statistical performance of optimization technique and found satisfactory. Keywords FIR filter design · Integrated optimization technique · Moth flame optimization · Powell’s pattern search
1 Introduction In the current scenario, the signal has a significant role in the digital signal processing (DSP) systems. Most of the signals have inherent noise and also get distorted with external noise; hence there is a need of digital filters to achieve the desired spectral characteristics. The basic building blocks of DSP systems are digital filters. Depending on the duration of the impulse response, digital filters are categorized into finite impulse
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Teena Mittal [email protected] Department of Electronics and Communication Engineering, Thapar Institute of Engineering and Technology, Patiala, Punjab 147004, India
Circuits, Systems, and Signal Processing
response (FIR) filter and infinite impulse response (IIR) filter [15]. The implementation of FIR filters uses non-recursive structures and having many desired advantages. The coefficients of linear phase FIR filter are symmetrically located around the central coefficient, and these filters are simple to design than IIR filters. The researchers have applied conventional methods to design digital filters such as window method and frequency sampling method. Various types of window function, i.e. Kaiser, Blackmann, Hanning, Hamming have been used as per filter specifications. In windowing method, for an ideal filter, the infinite length impulse response is approximated into a window of finite length to accomplish the real response [15, 25, 26]. However, due to this approximation, it does not permit the precise control of cut-off frequencies and the transition width. For the design of
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