Application of Classical Adaptive Filters in Speech Enhancement
Publish place: 9th Iranian Student Conference on Electrical Engineering
Publish Year: 1385
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
ISCEE09_036
تاریخ نمایه سازی: 13 اسفند 1386
Abstract:
In many applications of noise cancellation the changes in signal characteristics could be quite fast. This requires the utilization of adaptive
algorithms, which converge rapidly. Least mean square (LMS) and Normalized LMS (NLMS) adaptive filters have been used in a wide range of signal processing applications because of its simplicity in computation and implementation. The Recursive Least Squares (RLS) algorithm has established itself as the “ultimate” adaptive filtering algorithm in the sense that it is the adaptive filter exhibiting the best convergence behavior. Unfortunately, practical implementations of this algorithm are often associated with high computational complexity and/or poor numerical
properties. In this paper we have performed and compared these classical adaptive filters for attenuating noise in speech signals. In each algorithm, the optimum order of filter of adaptive algorithms have also been found through experiments.
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Authors
Mohammad Shams Esfand Abadi
Department of Electrical Engineering, Tarbiat Modares University, Tehran, Iran، Department of Electrical Engineering, Shahid Rajaee Teachers Training University, Tehran, Iran
Hossein Sirousi
Department of Electrical Engineering, Shahid Rajaee Teachers Training University, Tehran, Iran
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