Sparse Finite Impulse Response Low Pass Filter Design using Improved Firefly Algorithm
Savita Srivastava1, Atul Kumar Dwivedi2, Deepak Nagaria3
1Savita Srivastava, Department of ECE, BIET, Jhansi, India.
2Atul Kumar Dwivedi, Department of ECE, BIET, Jhansi, India.
3Deepak Nagaria, Department of ECE, BIET, Jhansi, India.
Manuscript received on September 22, 2019. | Revised Manuscript received on October 20, 2019. | Manuscript published on October 30, 2019. | PP: 2061-2066 | Volume-9 Issue-1, October 2019 | Retrieval Number: A9568109119/2019©BEIESP | DOI: 10.35940/ijeat.A9568.109119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this work, optimal sparse linear phase Finite impulse response filters are designed using swarm intelligence-based Firefly optimization algorithm. Filters are designed to meet the desired specification with fixed and variable sparsity. The objective function is formulated consisting of three parameters, i. e., maximum passband ripple, maximum stopband ripple and stopband attenuation. The effectiveness of the proposed method is evaluated in two stages. In first stage, the designed filters have been compared with non- sparse in terms of deviation in their specification. The Comparative analysis depicts that the proposed approach of sparse linear phase FIR filter design method performs better than the conventional methods without significantly deviating from the desired specification. The proposed designed filter is then implemented on xilinx ISE14.7(Vertex7) design environment and their performance is compared in terms of time delay, resource utilizaion and frequency of operation. In the second stage, designed sparse FIR filters are compared with earlier state of art sparse FIR filters design techniques.
Keywords: FIR Filters, Global Optimization, Firefly algorithm, Sparse