Vehicle Cabin Noise Cancellation Model Using Pre-Filter for Improved Convergence Rate and Better Stability Cover Image

Vehicle Cabin Noise Cancellation Model Using Pre-Filter for Improved Convergence Rate and Better Stability
Vehicle Cabin Noise Cancellation Model Using Pre-Filter for Improved Convergence Rate and Better Stability

Author(s): Janak Kapoor, Ajita Pathak, Manish Rai, G. R Mishra
Subject(s): Tourism, Transport / Logistics
Published by: Žilinská univerzita v Žilině
Keywords: active noise cancellation; adaptive algorithms; adaptive filtering; noise signal; convergence rate; SNR

Summary/Abstract: Adaptive algorithms are used in updating the filter coefficients for active noise cancellation applications in reduction of vehicle cabin noise. The performance of the adaptive algorithms in low-frequency noise cancellation depends on how efficiently it alters the filter coefficient to minimize the difference between the approximated signal and the original one. Here is proposed an active noise cancellation model, using the low pass fixed coefficient filter before the adaptive filter, in order to improve the performance of the adaptive algorithm. Convergence rate, SNR and error vector magnitude are analysed for of adaptive algorithm in support of our research results.

  • Issue Year: 25/2023
  • Issue No: 1
  • Page Range: 1-12
  • Page Count: 1
  • Language: English