An on-line transform domain Least Mean Square (LMS) algorithm based on a neural approach is proposed. A temporal Principal Component Analysis (PCA) network is used as an orthonormalization layer in the transform domain LMS filter. Since PCA learning is an on-line learning algorithm, an on-line transform domain LMS filter can be easily implemented. Moreover, a modified Kalman estimation, which c...

The Least Mean Square (LMS) algorithm and its variants are currently the most frequently used adaptation algorithms; therefore, it is desirable to understand them thoroughly from both theoretical and practical points of view. One of the main aspects studied in the literature is the influence of the step size on stability or convergence of LMS-based algorithms. Different publications provide dif...

In this paper constant modulus algorithm (CMA) and least mean square (LMS), kind of blind and nonblind algorithms used for adaptive beamforming are presented. These algorithms are embedded in smart antenna which calculates optimum weight vector that minimizes the total received power except the power coming from desired direction. The efficiency of CMA and LMS algorithms is compared on the basi...

This paper presents a simple and easy implementable Least Mean Square (LMS) type approach for frequency estimation of three phase power system in an unbalanced condition. The proposed LMS type algorithm is based on a second order recursion for the complex voltage derived from Clarke's transformation which is proved in the paper. The proposed algorithm is real adaptive filter with real parameter...

LMS algorithm is simple and is well suited for continuous transmission systems since it is a continuously adaptive algorithm. However, it is not known for its convergence speed in the presence of Gaussian, spatially white, of null mean and variance which has prompted people to use other complicated algorithms. In the above scenario LMS has maximum mean square error and minimum error stability. ...

In this work, the performance of two equalizers Least Mean Square (LMS) and Recursive Least Square (RLS) is observed by calculating the BER effect of Rician channels over low Doppler shift. AWGN is also added to the channel from -10 dB to 20 dB. The Bit Error Rate (BER) of 2, 4, 8-PSK (Phase Shift Keying) signals and 16, 64QAM (Quadrature Amplitude Modulation) over Rayleigh and Rician channel i...

Adaptive least mean square (LMS) filters with or without training sequences, which are known as training-based and blind detectors respectively, have been formulated to counter interference in CDMA systems. The convergence characteristics of these two LMS detectors are analyzed and compared in this paper. We show that the blind detector is superior to the training-based detector with respect to...

For demand of high data rates, enhanced system capacity and coverage, ITU made proposal for the standardization of next generation wireless communication systems, known as IMTAdvanced. To achieve these targets, a priori knowledge of the channel is required at the transmitter side. In this paper, three adaptive channel estimation techniques: Least Mean Square (LMS), Recursive Least Square (RLS) ...

A new adaptive step size adjustment least mean square (LMS) algorithm is presented in this paper. The proposed algorithm modified the existing LMS using the estimated output error as an important component for the modification of the step size. Experiment results demonstrate that application of the new algorithm leads to a significant gain in SNR (signal-to-noise ratio), thus visibly reduces th...

A CMOS switched-current adaptive filter architecture is presented. It is basically a finite impulse response (FIR) transversal filter adapted by using the Least-Mean-Square (LMS) adaptation algorithm. The design is based on delay and multiply-accumulator blocks. The implemented system can be switched to work either as an adaptive filter or as an FIR programmable filter. The adaptation signal ca...