Proposing a New Variable Window for better Side Lobe Reduction
Poonam Parmar1, Rahul Dubey2, Karuna Markam3
1Poonam Parmar, Department of Electronics Engineering, Madhav Institute of Technology and Science, Gwalior, India.
2Rahul Dubey, Department of Electronics Engineering, Madhav Institute of Technology and Science, Gwalior, India.
3Karuna Markam, Department of Electronics Engineering, Madhav Institute of Technology and Science, Gwalior, India.
Manuscript received on 18 June 2019 | Revised Manuscript received on 05 July 2019 | Manuscript published on 30 July 2019 | PP: 1107-1112 | Volume-8 Issue-9, July 2019 | Retrieval Number: I7792078919/19©BEIESP | DOI: 10.35940/ijitee.I7792.078919
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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: Digital signal processing is most widely used to process the signal. In digital signal processing filters are used to remove some unwanted constituents from aspired signal. Windowing is a scheme of finite impulse response filters. Present paper proposes a new versatile window function. It has two variable parameters first one is window span N and another changeable parameter is r. when the value of variable parameter r increases width of major lobe of window also increases with better side lobe reduction and vice versa. Gaussian window and Kaiser window are the well-known variable windows. This paper shows that the proposed window has more desirable results in comparison of Gaussian and Kaiser window with low power loss and better side lobe reduction. To achieve minimum power loss peak side lobe level should have to minimum. Proposed window has low peak side lobe level (-17.681dB) in comparison of Gaussian (-11.836dB) and Kaiser window (-6.9704dB). Proposed work shows that the proposed window has finer spectral characteristic then Gaussian and Kaiser window. FIR filter formed by applying proposed window has narrow -3dB bandwidth (2π×0.320 rad/sample) corresponding to FIR filter formed by using Gaussian and Kaiser window. Ripple ratio of FIR filter plotted by applying proposed window (-144.321dB) is less corresponding to FIR filter delineated by using Gaussian and Kaiser which indicates that the proposed window will give better side lobe rejection and reduce the aliasing problem. In the biomedical field noise present in ECG signal can also reduce by using proposed window.
Index Terms: FIR Filter, Gaussian Window, Kaiser Window, Spectral Characteristics of Window Function.
Scope of the Article: Software Defined Networking and Network Function Virtualization