Modified Normalized Least Mean Square (MNLMS) algorithm, which is a sign form of NLMS based on set-membership (SM) theory in the class of optimal bounding ellipsoid (OBE) algorithms, requires a priori knowledge of error bounds that is unknown in most applications. In a special but popular case of measurement noise, a simple algorithm has been proposed. With some simulation examples the performa...

A high quality acoustic subband echo canceller is developed based on a dual-filter structure and the fast recursive least squares (FRLS) algorithm. Methods for overcoming the instability problem of the FRLS algorithm and implementing it using the 32-bit fixed-point arithmetic are presented. A new tap-weight transfer method, which assures double talk detection, is proposed. Computer simulations ...

To overcome the tradeoff of the conventional normalized least mean square (NLMS) algorithm between fast convergence rate and low steady-state misalignment, this paper proposes a variable step size (VSS) NLMS algorithm by devising a new strategy to update the step size. In this strategy, the input signal power and the cross-correlation between the input signal and the error signal are used to es...

Training neural language models (NLMs) is very time consuming and we need parallelization for system speedup. However, standard training methods have poor scalability across multiple devices (e.g., GPUs) due to the huge time cost required to transmit data for gradient sharing in the backpropagation process. In this paper we present a sampling-based approach to reducing data transmission for bet...

We present a discussion of three adaptive filtering algorithms well known for their one-step termination property, in terms of their relationship with the minimal residual method. These algorithms are the normalized least mean square (NLMS), Affine Projection algorithm (APA) and the recursive least squares algorithm (RLS). The NLMS is shown to be a result of the orthogonality condition imposed ...

Acoustic echo cancellation represents one of the most challenging system identification problems. The most used adaptive filter in this application is the popular normalized least mean square (NLMS) algorithm, which has to address the classical compromise between fast convergence/tracking and low misadjustment. In order to meet these conflicting requirements, the step-size of this algorithm nee...

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...

Multi-rate digital signal processing techniques have been developed in recent years for a wide range of applications, such as speech and image compression, statistical and adaptive signal processing and digital audio. Multi-rate statistical and adaptive signal processing methods provide solution to original signal reconstruction, using observation signals sampled at different rates. In this stu...

This work presents exact tracking analysis of the ε-normalized least mean square (ε-NLMS) algorithm for circular complex correlated Gaussian input. The analysis is based on the derivation of a closed form expression for the cumulative distribution function (CDF) of random variables of the form [||ui||2D1 ][ε+ ||ui|| 2 D2 ] −1. The CDF is then used to derive the first and second moments of these...

In this paper, event related potential (ERP) generated due to hand movement is detected through the adaptive noise canceller (ANC) from the electroencephalogram (EEG) signals. ANCs are implemented with least mean square (LMS), normalized least mean square (NLMS), recursive least square (RLS) and evolutionary algorithms like particle swarm optimization (PSO), bacteria foraging optimization (BFO)...