سال انتشار: ۱۳۸۵

محل انتشار: نهمین کنفرانس دانشجویی مهندسی برق

تعداد صفحات: ۶

نویسنده(ها):

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

چکیده:

In many applications of noise cancellationthe 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 filtershave 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 eachalgorithm, the optimum order of filter of adaptive algorithms have also been found through experiments.