We propose a two-stage adaptive filtering process for canceling narrowband interference from a wideband signal process, based on a reference signal consisting of a Doppler shifted version of the interference. The first stage uses the timevarying behavior of NLMS with large step-size to produce an estimate of the interference signal, in which the Doppler shift is mitigated. The second stage uses...

The performance of linear acoustic echo cancelers degrades if nonnegligible nonlinear distortion is introduced into the echo path as, e.g., caused by low-cost loudspeaker systems driven at high volume. Adaptive second-order Volterra filters are known to effectively model nonlinear acoustic echo paths. In this contribution we propose an extension of the proportionate NLMS (PNLMS) to second-order...

The proportionate normalized least mean square (PNLMS) algorithm and its variants are by far the most popular adaptive filters that are used to identify sparse systems. The convergence speed of the PNLMS algorithm, though very high initially, however, slows down at a later stage, even becoming worse than sparsity agnostic adaptive filters like the NLMS. In this paper, we address this problem by...

This paper extends the recently introduced variable step-size (VSS) approach to the family of adaptive filter algorithms. This method uses prior knowledge of the channel impulse response statistic. Accordingly, optimal stepsize vector is obtained by minimizing the mean-square deviation (MSD). The presented algorithms are the VSS affine projection algorithm (VSS-APA), the VSS selective partial u...

In order to achieve fast convergence and less computation for adaptive filters, a joint method combining a whitening process and the NLMS algorithm is a hopeful approach. One of them is to combine a lattice predictor and a transversal filter supervised by the NLMS algorithm. However, the filter coefficient adaptation is very sensitive to the reflection coefficient fluctuation. In this paper, th...

In this article a high resolution database of Head-Related Impulse Responses (HRIRs) and anthropometric parameters for 35 human subjects and two KEMAR manequins is introduced. The HRIRs were computed using Normalized Least Mean Square (NLMS) adaptive filtering. The NLMS method has no audible drawbacks compared to well-established HRIR estimation approaches (MLS and Exponetnial Sweep method) whi...

In present stereo audio system is a most popular audio system for different purposes. Now a day’s stereo system is commonly used in communication and other purposes. Moreover Normalized Least Mean Square (NLMS) based adaptive filtering is an effective filtering process in case of communication and other applications. However adaptive filtering is an adaptive filter process to cancel out the noi...

In this paper Adaptive filter is designed and simulated using different algorithms for noise reduction in different signals. The developed filter has been analyzed using Least Mean Square (LMS), Normalized Least Mean Square (NLMS) and Recursive Least Squares (RLS) algorithms for sinusoidal, chirp and saw-tooth signals. The performance of developed filter has been compared interms of Rate of Con...

This paper provides analysis of kepstrum (known elsewhere as complex cepstrum) and its real-time application to noise cancellation. The method uses kepstrum estimation for identification of the ratio of acoustic path transfer functions between two microphones and efficient processing technique for real-time processing. It is applied to the front-end of speech enhancement method, the Griffiths a...

Acoustic feedback is a common phenomenon that occurs during hearing aid use, limiting the maximum gain can provide. Effective cancellation of acoustic an essential feature aids. However, due to complex environments in which aids are used and frequently changing path, it difficult for existing adaptive filter-based algorithms balance both convergence speed steady-state error. For this reason, ba...