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  • 标题:Multiple Processes for Least Mean Square Adaptive Algorithm on Roadway Noise Cancelling
  • 本地全文:下载
  • 作者:Sri Arttini Dwi Prasetyowati ; Adhi Susanto
  • 期刊名称:International Journal of Electrical and Computer Engineering
  • 电子版ISSN:2088-8708
  • 出版年度:2015
  • 卷号:5
  • 期号:2
  • 页码:355-360
  • DOI:10.11591/ijece.v5i2.7516
  • 语种:English
  • 出版社:Institute of Advanced Engineering and Science (IAES)
  • 摘要:Noise is a problem often found in daily life. Noise also make people could not concentrate to do their work. Efforts to reduce noise have been proposed, but, due to variety of the noise’s characteristics, every noise problem requires different solution. This research aim to cancel the vehicle’s noise while maintaining the information heard. These conditions happened in the hospitals classrooms, or work room near the roadway. The vehicle’s noise change very fast, so the adaptive system is the good solution candidate for solving this problem. On the beginning, the simulation process had the trouble with the iterations. Matlab software only can execute the certain range of iteration. It could not cancel the noise, even the information becomes criptic. The problem is how to cancell the vehicle’s noise with the restriction software and still manage the important information. This research will modify the LMS adaptive algorithm so that the iteration could be done by the system and the main goal of the research could be reached. The modification of the algorithm is based on the filter length (L) used to adapt with the noise. Therefore, this research conducted simulation of the Adaptive Noise Cancelling with two process steps. The output of the first adaptive process have the.same characteristics with the noise that would be cancelled, thus the first adaptive process have the error near to zero. The second adaptive process changes the input by the output of the first process and mix the information into the noise. Error occured in the final process is the information heard as the dominant output.
  • 关键词:Instrumentation and Control;Filter length;LMS adaptive; Noise Cancelling
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