The least mean square algorithm

The paper has proposed an adaptive filter using particle swarm optimization algorithm (PSO) and its application to cancelled white noise. This is a new method to obtain signals with higher quality than previous adaptive filter methods such as Least Mean Squares (LMS) filter, Normalized Least Mean Square method (NLMS).

3p viericschmid 12-01-2022 8 0   Download

Mm-wave is currently of interest due to its ability to enhance large bandwidth, which can fully meet the speed of 5G information systems. The beamforming techniques are studied for this wave such as beam weights updating at the receiver to ensure the fastest convergence rate of the weighting algorithm. We need to specify algorithms such as mean least squares (LMS), recursive least squares (RLS), sampling matrix inverse (SMI), conjugate gradient methods (CGM). There are many articles related to the comparison of these algorithms on convergence weighting speed, transmission capacity.

9p vilarrypage 19-11-2021 17 2   Download

This paper studies the effects of nonlinear distortion of Low Noise Amplifier (LNA) in the multichannel direct-RF sampling receiver (DRF). The main focus of our work is to study and compare the effectiveness of the different adaptive compensation algorithms, including the inverse-based and subtract-based Least Mean Square (LMS) algorithm with a fixed and variable step size. The models for the compensation circuits have been analytically derived. As the major improvements, the effectiveness of the compensation circuits under the ADC quantization noise effect is evaluated.

12p trinhthamhodang9 10-12-2020 13 1   Download

The LMS algorithm is known as a simple algorithm, which is fast computation time and the computation results are quite satisfying. In this study, the authors used Simulink software on Matlab. In general, this research is divided into three stages, namely modeling multipaths communication channels as an adaptive system, designing an adaptive system model on Simulink, and designing a simulation of 250 iterations.

7p lucastanguyen 28-05-2020 6 0   Download

The data pertaining to 623 purebred and 202 Fec-B gene introgressed Kashmir Merino lambs born to 25 and 11 sires, respectively were analyzed with the Mixed Model Least Squares and Maximum Likelihood algorithms, PC-2 version computer programme (Harvey. 1990) to assess the effect of Fec-B gene introgression and some non-genetic factors on performance traits of Kashmir Merino sheep.

6p cothumenhmong3 22-02-2020 24 2   Download

The combination of the kernel trick and the least-mean-square (LMS) algorithm provides an interesting sample by sample update for an adaptive equalizer in reproducing Kernel Hilbert Spaces (RKHS), which is named here the KLMS. This paper shows that in the finite training data case, the KLMS algorithm is well-posed in RKHS without the addition of an extra regularization term to penalize solution norms.

4p sabiendo 06-02-2020 12 0   Download

Multivariate Curve Resolution with Alternating Least Squares (MCR-ALS) is a curve resolution method based on a bilinear model which assumes that the observed spectra are a linear combination of the spectra of the pure components in the system. The algorithm steps include the determination of the number of components by rank analysis methods, initial estimates for the concentrations and/or spectra and an iterative optimization. Sometimes, suitable results may not be achieved when MCR-ALS is applied. One reason for this is the importance of the initial estimates of the spectral profiles.

8p kequaidan1 16-11-2019 16 0   Download

This paper discusses predicting attendance at Major League Soccer events using data from the 2014 and 2015 seasons. Panel data is obtained for each team, season, and weather category. A traditional least squared dummy variable linear regression technique is used along with three machine learning algorithms – random forest, M5 prime, and extreme gradient boosting. Extreme gradient boosting provides superior results with respect to out-of-sample root mean square error statistics.

8p guestgreat 16-05-2019 32 0   Download

In this paper we present an adaptive filter for denoising the ECG signal based on Leaky Normalized Least Mean Square (LNLMS) algorithm. The adaptive filter essentially minimizes the mean squared error between a primary input, which is the noisy ECG, and a reference input, which is either noise that is correlated in some way with the noise in the primary input or a signal that is correlated only with ECG in the primary input.

4p girlsseek 27-02-2019 20 0   Download

The aim of this paper is to implement various adaptive noise cancellers (ANC) for speech enhancement based on gradient descent approach, namely the least-mean square (LMS) algorithm and then enhanced to variable step size strategy. In practical application of the LMS algorithm, a key parameter is the step size. As is well known, if the step size is large, the convergence rate of the LMS algorithm will be rapid, but the steady-state mean square error (MSE) will increase. On the other hand, if the step size is small, the steady state MSE will be small, but the convergence rate will be slow.

5p girlsseek 27-02-2019 25 0   Download

In this paper, datasets are collected from ERPLAB and journals provided available datasets with the stimulus of sound and light. Using adaptive noise cancellation (ANC) combined with LMS algorithm the waves P300 of ERP were detected and separated.

8p sansan2 26-05-2018 21 0   Download

This paper proposes a design of an adaptive beamformer for arbitrarily Uniformly spaced Linear Array (ULA) antennas. Least Mean Square (LMS), a prevalent adaptive beamforming algorithm, has been employed in the beamformer for the ULA antennas. A procedure has been introduced to validate the proposed design. Applying the proposal, a LMS based adaptive beamformer for 8×1 ULA antennas has been built and implemented on Xilinx FPGA.

8p truongtien_09 10-04-2018 28 4   Download

Adaptive Filters Adaptive structures The least mean square (LMS) algorithm Programming examples using C and TMS320C3x code Adaptive filters are best used in cases where signal conditions or system parameters are slowly changing and the filter is to be adjusted to compensate for this change. The least mean square (LMS) criterion is a search algorithm that can be used to provide the strategy for adjusting the filter coefficients. Programming examples are included to give a basic intuitive understanding of adaptive filters. ...

28p doroxon 16-08-2010 80 6   Download

Adaptive Filters • • • Adaptive structures The least mean squares (LMS) algorithm Programming examples for noise cancellation and system identification using C code Adaptive filters are best used in cases where signal conditions or system parameters are slowly changing and the filter is to be adjusted to compensate for this change. The least mean squares (LMS) criterion is a search algorithm that can be used to provide the strategy for adjusting the filter coefficients. Programming examples are included to give a basic intuitive understanding of adaptive filters. 7.

23p khinhkha 30-07-2010 105 6   Download