SUMMARY We propose a novel adaptive filtering scheme named metric-combining normalized least mean square (MC-NLMS). The proposed scheme is based on iterative metric projections with a metric designed by combining multiple metric-matrices convexly in an adaptive manner, thereby taking advantages of the metrics which rely on multiple pieces of information. We compare the improved PNLMS (IPNLMS) a...

Neural language models (NLMs) have been able to improve machine translation (MT) thanks to their ability to generalize well to long contexts. Despite recent successes of deep neural networks in speech and vision, the general practice in MT is to incorporate NLMs with only one or two hidden layers and there have not been clear results on whether having more layers helps. In this paper, we demons...

The use of partial update adaptive filters for stereophonic acoustic echo cancellation is investigated. The MMax-NLMS algorithm is studied in this context and its inherent robustness to subsampling of the tap-input vector is demonstrated. It is proposed to employ the subsampling of the tap input vector, that is intrinsic to partial update schemes, to decorrelate the two tap-input vectors of the...

To estimate multiple-input multiple-output (MIMO) channels, invariable step-size normalized least mean square (ISSNLMS) algorithm was applied to adaptive channel estimation (ACE). Since the MIMO channel is often described by sparse channel model due to broadband signal transmission, such sparsity can be exploited by adaptive sparse channel estimation (ASCE) methods using sparse ISS-NLMS algorit...

In this paper, we address the robustness, in the sense of l2-stability, of the set-membership normalized least-meansquare (SM-NLMS) and the set-membership affine projection (SM-AP) algorithms. For the SM-NLMS algorithm, we demonstrate that it is robust regardless of the choice of its parameters and that the SM-NLMS enhances the parameter estimation in most of the iterations in which an update o...

In this paper, a new encoding algorithm of spectral envelope based on NLMS in G.729.1 for VoIP is proposed. In the TDAC part of G.729.1, the spectral envelope and MDCT coefficients extracted in the weighted CELP coding error (lower-band) and the higher-band input signal are encoded. In order to reduce allocation bits for spectral envelope coding, a new quantization algorithm based on NLMS is pr...

In this paper, we propose improved versions of normalized least mean square (NLMS) algorithm: single and multiple -variable step size normalized least mean square (VSSNLMS) algorithms for echo cancellation. The presented algorithms exhibit faster convergence rate in comparison to NLMS algorithm. Simulation results employing standard figure of merits show how the algorithms perform better than N...

and SNLMS is obvious from Fig. 1. Note that the performance of the proposed algorithm is quite comparable with the NLMS algorithm. The slow convergence speed of the SBNLMS and SNLMS algorithms relative to the NLMS algorithm in Fig. 1 is not surprising since the convergence of the SBNLMS and SNLMS algorithms is expected to be eight times slower than the NLMS algorithm. On the other hand, the str...