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The ℓp norm-constrained proportionate normalized least-mean-square (LP-PNLMS) using the modified filtered-x structure is proposed for active noise control. It is shown that better performance is obtained for primary and secondary paths having a wide range of sparseness levels when compared with competing sparsity-inducing algorithms at a price of moderate complexity increase.
This paper addresses the problem of acoustic noise reduction and speech enhancement in new telecommunication systems by adaptive filtering algorithms. We propose a new two-channel forward BSS algorithm based on signal prediction to give an automatic algorithm with a very nice behavior at the output. This algorithm is called the two-channel fast normalized least mean square (TCFNLMS) algorithm. This...
In several previous works, the two-channel adaptive filtering algorithms have been proposed and combined with forward-and-backward blind source separation structures for acoustic noise reduction and speech enhancement. Recently in [1], we have proposed a new two-channel subband forward algorithm (2CSF) for acoustic noise reduction. The main drawback of this algorithm is its poor performance in steady...
The estimation value of time delay between two leakage signals is the main factor affecting the accuracy of leak location during the pipeline leak location. How to quickly find out the delay time and improve the positioning accuracy are difficulties. In this paper, the basic principle of leak location and LMS adaptive filtering algorithm were analyzed, then for computational complexity and the positioning...
A novel adaptation strategy is proposed for Acoustic Echo Cancellation (AEC). The new algorithm firstly partitions the adaptive filter into several blocks and the successive blocks with the maximum h norm are considered to be the active blocks. Then the coefficients of the active blocks are adapted with large update probability to ensure the identification accuracy while the zero coefficients are...
Based on the variable step-size afïîne projection algorithm, the idea of multiple forgetting factors and variable projection order is proposed. On the one hand, the accurate estimation of error energy is realized in order to achieve faster convergence rate and lower final misalignment. On the other hand, the reduction of computational complexity can be achieved. The simulation results show that the...
This paper addresses the problem of speech quality enhancement and acoustic noise reduction by adaptive filtering algorithms. In this paper, we propose a new version of the set-membership partial-update normalized least mean square (SM-PU-NLMS) algorithm. The proposed algorithm is based on the use of the cross-correlation of the output error signal and the noisy to control the variable-step-size in...
This paper proposes a new method of reducing the steady-state error for the Affine Projection Algorithm (APA) using Error Reduction Factor (ERF) to yield Error Reduction Affine Projection Algorithm (ER-APA). The proposed method is very simple but highly effective. In the paper, we analyze the ER-APA for calculating theoretical filter convergence. Through experiments, it is shown that the ER-APA sufficiently...
Acoustic Echo Cancellation (AEC) is a signal processing method which ensures a pleasant duplex communication in hands free system by suppressing the echo signal. Acoustic Echo is a major stumbling factor in maintaining quality and intelligibility of speech signal. Poor quality of speaker and low cost amplifier in typical mobile equipment introduce the non-linearity in the acoustic echo signal. In...
We propose a polarization tracking and channel equalization scheme for PM-16QAM signals based on radius-directed recursive least squares adaptive filter. The simulation results prove that the algorithm has faster convergence speed and tracking speed compared to traditional RDE algorithm.
This paper proposes a new and very simple method to perform identification of nonlinearities in systems that are supposed to be linear. The improvement with respect to the previous approaches lies in the low computational complexity of the solution and the convenient possibility of online evaluation. Simulation results show that the proposed method provides good performance in terms of coefficients...
This paper presents a novel nonlinear adaptive filter method, namely, Hammerstein adaptive filter with single feedback under minimum mean square error (HAF-SF-MMSE). A single delayed output is incorporated into the estimation of the current output based on minimum mean square error criterion, and therefore the history information of output is considered. Moreover, hybrid learning rates and adaptive...
Multimedia files, either video or audio, could greatly influence the final verdict of a trial when accepted as evidence. The abundance of free editing software available nowadays make forgeries a very easy operation. Audio messages, even if authentic, in some cases, can be heavily masked by other signals and declared unusable. This paper presents the investigations on the performance of the affine...
This paper presents a practical overview on the adaptive algorithms used in acoustic echo cancellation (AEC) systems. It describes first the Least Mean Square (LMS) family and the variable step size (VSS) corresponding versions. It includes also the Recursive Least Squares (RLS) family, focusing on the benefits introduced by this class of adaptive algorithms (e.g., faster convergence). Finally, it...
Photoplethysomographic (PPG) signal is crucial for non-invasive monitoring of heart rate. It is acquired by using pulse oximeter that are prone to artifacts. A major application of this technique is monitoring the heart rate during physical exertion. Extraction of heart rate (HR) from the PPG in this case is difficult due to the strong motion related artifacts. This paper proposes an efficient method...
Speech enhancement using adaptive filtering methods are known to give good signal recovery from the noisy speech signal. Among these, Least Mean Square (LMS) and Recursive Least Squares (RLS) algorithms are more popular. These algorithms have a constraint that correlating noise should be given as the reference signal for denoising. Therefore in all the adaptive algorithms, two microphones are used,...
The ZA-NLMS (for zero-attractor) represents arguably the seminal sparsity-aware gradient adaptive algorithm. As it is constraint by the ℓ1-norm of the filter weights, the underlying problem turns convex, hence with unique solution (in expected sense). Despite these friendly properties, the algorithm convergence and, more important, the best-performing sparsity tradeoff are yet to be effectively studied...
In real time situations, IIR filter typically works in an under-modelling situation for a system where infinite impulse response (IIR) filter of the system is prodigiously long. In this anterior work there is an inadequate-length of fixed least-mean-square (FLMS), the convergence based on step value can be improved. Various methods for FLMS algorithm had been presented. This paper provides an Evolutionary...
Estimation of small tap-coefficients of large sparse system using μ-law based proportionate normalized least square (MPNLMS) algorithm yields slow converges, since the proportionality of these coefficients is ignored in the updated process. The individual activation factor-MPNLMS (IAF-MPNLMS) algorithm solves this problem by assigning new gain distribution factor while updating the tap-coefficients...
Adaptive efficient mechanism eliminates varying environmental noise embedded in speech signals, since the eigenvalue spread has a great influence on the convergence behavior of adaptive algorithms. The inefficient least mean square (LMS) algorithm for ill-conditioned signals, with high eigenvalue spread in the autocorrelation matrix, hence slow convergence and degraded signal quality are observed...
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