Step-Size Adjustments of NLMS Algorithm for Acoustic Echo Cancellation
碩士 === 國立交通大學 === 電信工程系所 === 92 === The most often used algorithm for acoustic echo cancellation is normalized least mean square (NLMS) algorithm due to its simplicity and robustness. However, the major drawback of NLMS algorithm is its slow convergence rate due to its constant step-size. We propose...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2004
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| Online Access: | http://ndltd.ncl.edu.tw/handle/9532hj |
| Summary: | 碩士 === 國立交通大學 === 電信工程系所 === 92 === The most often used algorithm for acoustic echo cancellation is normalized least mean square (NLMS) algorithm due to its simplicity and robustness. However, the major drawback of NLMS algorithm is its slow convergence rate due to its constant step-size. We propose a new approach of adjusting step-size called optimum step-size NLMS. The word “optimum” means the step-size can provide the minimum tap coefficient error mean square error at each iteration step which leads the fastest convergence rate than other algorithms. Each tap has its individual time-variant step-size which adjusts with tap coefficient error variance. We analyze double talk detector proposed by J. C. Liu. It uses the concept of counter to record number of abrupt events happened during a short period when an abrupt change in residual echo. Echo return loss enhancement (ERLE) is used to indicate the cost of using different threshold. Finally, computer simulations will be presented to support the analysis.
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