Hum Noise Reduction using Novel Complementary Pair VSSLMS Algorithm
Saurabh R Prasad1, Anushka D Kadage2, Sachin M Karmuse3, Shrinivas A Patil4, Bhalchandra B Godbole5
1Saurabh R Prasad*, Assistant Professor, Department of Electronics and Telecommunication, KIT College of Engineering, Kolhapur, India.
2Anushka D Kadage, Assistant Professor, Department of Digital Communication and Digital Signal Processing, Visvesvaraya Technological University, Belgaum, Karnataka, India.
3Sachin M Karmuse, Assistant Professor, Department of Computer Programming, Visvesvaraya Technological University, Belgaum, Karnataka, India.
4Shrinivas A Patil, Professor, Department of Electronics and Telecommunication Engineering, DKTE Society’s Textile and Engineering Institute, Ichalkaranji, India.
5Dr Bhalchandra B Godbole, Associate Professor, Department of Electronics Engineering, Karmaveer Bhaurao Patil College of Engineering, Mumbai, Maharashtra, India.
Manuscript received on September 22, 2019. | Revised Manuscript received on October 20, 2019. | Manuscript published on October 30, 2019. | PP: 1720-1727 | Volume-9 Issue-1, October 2019 | Retrieval Number: A1363109119/2019©BEIESP | DOI: 10.35940/ijeat.A1363.109119
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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: This paper presents a novel Complementary Pair Variable Step-size (CPVSS) Least Mean Square Algorithm which is implemented for active noise cancellation application. The result presents the effect of filtration to remove the 50 Hz ac hum noise from the 500 Hz audio tone. Discrete Fourier Transform, Short Time Fourier Transform, and Welch Periodogram of the noisy signal and filtered signal have been presented which shows effective improvement in SNR. The simulation study has shown the superiority of this algorithm over other algorithms under consideration.
Keywords: Active noise cancellation, complementary pair variable stepsize LMS, hum noise, short time Fourier transform.