Survey of Sparse Adaptive Filters for Acoustic Echo Cancellation

Abstract

Abstract-This paper reviews the existing developments of adaptive methods of sparse adaptive filters for the identification of sparse impulse response in both network and acoustic echo cancellation from the last decade. A variety of different architectures and novel training algorithms have been proposed in literature. At present most of the work in echo cancellation on using more than one method. Sparse adaptive filters take the advantage of each method and showing good improvement in the sparseness measure performance. This survey gives an overview of existing sparse adaptive filters mechanisms and discusses their advantages over the traditional adaptive filters developed for echo cancellation.

Analysis of Abdominal ECG Signal for Fetal Heart Rate Estimation Using Adaptive Filtering Technique

“…The maternal ECG signal obtained at the probe of the mother's chest cavity is used as the reference signal to the input abdominal ECG signal obtained at the probe of the womb. Recently this technique was used for acoustic echo cancellation [15], GPS multipath error estimation and mitigation [16] and estimation of hyper-complex quantity (rotor) able to describe rotations in any dimension [17].…”

Variable partial-update NLMS algorithms with data-selective updating

“…The computational complexity is one of the most important characteristics in several applications of adaptive filtering, i.e., in the acoustic echo cancellation [1] and in the adaptive channel estimation for communication systems [2]. Several algorithms have been proposed to reduce the computational complexity of the NLMS algorithm, such as the partial-update (PU) algorithms [3][4][5] which update only part of the filter coefficients.…”