In this paper, echo cancellation is done using genetic algorithm (GA). The genetic algorithm is implemented by two kinds of crossovers; heuristic and microbial. A new procedure is proposed to estimate the coefficients of adaptive filters used in echo cancellation with combination of the GA with Least-Mean-Square (LMS) method. The results are compared for various values of LMS step size and diff...

The wavelet transform-domain least-mean square (WTDLMS) algorithm uses the self-orthogonalizing technique to improve the convergence performance of LMS. In WTDLMS algorithm, the trade-off between the steady-state error and the convergence rate is obtained by the fixed step-size. In this paper, the WTDLMS adaptive algorithm with variable step-size (VSS) is established. The step-size in each subf...

An adaptive minimummean-square error (MMSE) array receiver based on the fuzzy-logic recursive least-squares (RLS) algorithm is developed for asynchronous DS-CDMA interference suppression in the presence of frequency-selective multipath fading. This receiver employs a fuzzy-logic control mechanism to perform the nonlinear mapping of the squared error and squared error variation, denoted by (e2,Δ...

A new method is introduced,for the identification of Wiener model. The Wiener model consists of a linear,dynamic! block followed by a static nonlinearity. The nonlinearity and the linear dynamic part in the model are identified by using radial basis functions neural network (RBFNN) and autoregressive moving average (ARMA) model, respectively. The new algorithm makes use of the well known mappin...

The increase in life expectancy, according to the World Health Organization, is a fact, and with it rises incidence of age-related neurodegenerative diseases. most recurrent symptoms are those associated tremors resulting from Parkinson’s disease (PD) or essential (ETs). main alternatives for treatment these patients medication surgical intervention, which sometimes have restrictions side effec...

This paper compares two adaptive methods of de-convolving the instrument responses from seismic events against the standard single-degree-of-freedom (SDOF) method. The Least Mean Squares (LMS) algorithm and the square root, Recursive Least Squares (RLS) algorithm are considered and investigated using three seismic events. Both adaptive methods do not assume any knowledge of instrument data, but...

1 Abstract In some recent papers new algorithms for blind adaptive equalization were proposed. These algorithms are based on the stochastic gradient method and thus can be regarded as a blindd counterpart to the classic LMS-(least mean squares-) algorithms. It is well-known that these algorithms show relatively slow convergence speed. The classic solution to get fast convergence is the RLS-(rec...

 Abstract— In many application of noise cancellation, the changes in signal characteristics could be quite fast. This requires the utilization of adaptive algorithms, which converge rapidly. Least Mean Squares (LMS) and Normalized Least Mean Squares (NLMS) adaptive filters have been used in a wide range of signal processing application because of its simplicity in computation and implementatio...

A simple model characterizing the convergence properties of an adaptive digital lattice filter using gradient algorithms has been reported [ 11. This model is extended to the least mean square (LMS) lattice joint process estimator [SI, and to the least squares (LS) lattice and “fast” Kalman algorithms [9] -[16]. The models in each case are compared with computer simulation. The single-stage LMS...

The least mean squares (LMS) method for linear least squares problems differs from the steepest descent method in that it processes data blocks one-by-one, with intermediate adjustment of the parameter vector under optimization. This mode of operation often leads to faster convergence when far from the eventual limit and to slower (sublinear) convergence when close to the optimal solution. We e...