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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Shrawankar, Urmila Thakare, Vilas |
| Copyright Year | 2010 |
| Description | Author affiliation: G H Raisoni College of Engg. Nagpur, India (Shrawankar, Urmila) || PG Dept. of Computer Science, SGB Amravati University, Amravati, India (Thakare, Vilas) |
| Abstract | Traditionally, adaptive filters have been deployed to achieve AEC by estimating the acoustic echo response using algorithms [1,2] such as the Normalized Least-Mean-Square (NLMS) algorithm. Several approaches have been proposed over recent years to improve the performance of the standard NLMS algorithm in various ways for AEC. These include algorithms based on Time-Domain, Frequency Domain, Fourier Transform [7], Wavelet Transform [8] Adaptive Schemes, Proportionate Schemes, Proportionate Adaptive Filters, Combination Schemes, Block-Based Combination, Subband Adaptive Filtering, Uniform Over-Sampled DFT Filter Banks, Subband Over-Sampled DFT Filter Banks, Volterra Filters, Variable Step-Size (VSS) algorithms [9,10], Data Reusing Techniques [11,12], Partial Update Adaptive Filtering Techniques [13,14] and Subband (SAF) Schemes [15]. These approaches aim to address issues in echo cancellation including the performance with noisy input signals, Time-Varying echo paths and computational complexity. In contrast to these approaches, Sparse Adaptive algorithms have been developed specifically to address the performance of adaptive filters in sparse system identification. In this paper we have discussed some AEC algorithms followed by comparative study with respective to step-size, convergence and performance. |
| Starting Page | 489 |
| Ending Page | 494 |
| File Size | 237858 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424468898 |
| e-ISBN | 9781424468904 |
| DOI | 10.1109/TENCON.2010.5686709 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-11-21 |
| Publisher Place | Japan |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Convergence Adaptive filters Echo cancellers Dispersion Approximation algorithms Filter bank Sparseness-Controlled Algorithms Acoustic Echo Cancellation Speech Recognition System Noisy Environment Proportionate-Type Algorithms |
| Content Type | Text |
| Resource Type | Article |
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