Area and Energy Efficient Method Using AI for Noise Cancellation in Ear Phones
Active Noise Cancellation; Active Noise Reduction; Digital Signal Processing; Normalized Least Mean Square; Recursive Least Square and Block LMS
Adaptive filters are suitable for most of the Digital Signal Processing (DSP) applications such as channel equalization, noise cancellation, echo cancellation, channel estimation and system identification. Nowadays due to the advancement in semiconductor technology, the need for Active Noise Cancellation (ANC) headphones in compact devices is increased. The major idea behind this proposed work is to design an area and energy efficient novel adaptive filter suitable for in-ear headphones by combining Normalized Least Mean Square (NLMS) and Block LMS (BLMS). The proposed filter is designed and simulated using Xilinx ISE 13.2. The simulation results shows that the proposed design mitigates the unwanted noises in various frequency bands. 2023 IEEE.
Manikandan R.; Ramkumar S.; Prabhakaran M.
International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2023 - Proceedings, pp. 117-121.
Institute of Electrical and Electronics Engineers Inc.
https://doi.org/10.1109/ICSSAS57918.2023.10331813 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85181067301&doi=10.1109%2fICSSAS57918.2023.10331813&partnerID=40&md5=463fa972febd5d576d8b59dbf93e7068
Manikandan R., School of Business and Management Christ (Deemed to Be University), Department of Lean Operations and Systems, Karnataka, Bengaluru, India; Ramkumar S., School of Sciences, Christ (Deemed to Be University), Department of Computer Science, Karnataka, Bengaluru, India; Prabhakaran M., Alliance College of Engineering and Design, Alliance University, Department of Computer Science and Engineering, Karnataka, Bengaluru, India