Adaptive Noise Cancellation Using Multirate Techniques

Signal Processing

In many application of noise cancellation, the changes in signal characteristics could be quite fast. This requires the utilization of adaptive algorithms, which converge rapidly. Least Mean Squares (LMS) and Normalized Least Mean Squares (NLMS) adaptive filters have been used in a wide range of signal processing application because of its simplicity in computation and implementation. Unfortunately, practical implementations of the algorithm are often associated with high computational complexity and/or poor numerical properties. Recently adaptive filtering was presented, have a nice tradeoff between complexity and the convergence speed. Here LMS is introduced and used for noise cancellation in audio signal ,speech signal. This paper presents development of a new adaptive structure based on multirate filter and testing the same for deterministic, speech and music signals. A new class of FIR filtering algorithm based on the multirate approach is proposed. They not only reduce the computational complexity in FIR filtering, but also retain attractive implementation related properties such as regularity and multiply-andaccumulate (MAC)-structure. By virtue of the advantages of multirate FIR filtering algorithm, the proposed scheme can reduce the required computational complexity and reserve the MAC structure. It is observed that the convergence rate and steady state error is improved. An application of this approach in Adaptive Noise Canceller is considered

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