Tracking analysis of the normalized LMS algorithm without the independence and small step size assumptions

2009 ◽  
Author(s):  
Eweda Eweda
Keyword(s):  
Lms Algorithm ◽  
Small Step ◽  
Step Size ◽  
Small Step Size ◽  
Normalized Lms

scholarly journals The RSC Chromatin Remodeling ATPase can Translocate DNA with High Force and Small Step Size

2011 ◽  
Vol 100 (3) ◽  
pp. 354a
Author(s):  
George Sirinakis ◽  
Cedric R. Clapier ◽  
Ying Gao ◽  
Ramya Viswanathan ◽  
Bradley R. Cairns ◽  
...  
Keyword(s):  
Chromatin Remodeling ◽  
Small Step ◽  
Step Size ◽  
Small Step Size

scholarly journals The RSC chromatin remodelling ATPase translocates DNA with high force and small step size

2011 ◽  
Vol 30 (12) ◽  
pp. 2364-2372 ◽  
Author(s):  
George Sirinakis ◽  
Cedric R Clapier ◽  
Ying Gao ◽  
Ramya Viswanathan ◽  
Bradley R Cairns ◽  
...  
Keyword(s):  
Chromatin Remodelling ◽  
Small Step ◽  
Step Size ◽  
Small Step Size

scholarly journals A New Variable Step-Size NLMS Algorithm and its Performance Evaluation in Echo Cancelling Applications

2011 ◽  
Vol 9 (03) ◽  
Author(s):  
F. M. Casco-Sánchez ◽  
R. C. Medina-Ramírez ◽  
M. López-Guerrero
Keyword(s):  
Cross Correlation ◽  
Echo Cancellation ◽  
Lms Algorithm ◽  
Variable Step Size ◽  
Step Size ◽  
Filter Output ◽  
Nlms Algorithm ◽  
Variable Step ◽  
Size Adjustment ◽  
Normalized Lms

In this work we introduce a variable step-size normalized LMS algorithm for adaptive echo cancellation in a FIRstructure. In the proposed scheme, the step-size adjustment is controlled by using the square of the cross-correlationbetween the squared output error and the adaptive filter output. The proposed algorithm (that we call VSSSC aftervariable step size based on the squared cross-correlation) was evaluated using white noise and speech signals.Simulation results show that our proposal achieves better performance than similar algorithms in single and doubletalk. The proposed algorithm can be used in a number of applications such as in echo reduction for long-haul voicecommunications.

An ALO Optimized Adaline Based Controller for an Isolated Wind Power Harnessing Unit

Designs ◽  
2021 ◽  
Vol 5 (4) ◽  
pp. 65
Author(s):  
Amritha Kodakkal ◽  
Rajagopal Veramalla ◽  
Narasimha Raju Kuthuri ◽  
Surender Reddy Salkuti
Keyword(s):  
Wind Power ◽  
Optimization Method ◽  
Optimization Techniques ◽  
Lms Algorithm ◽  
Mean Square ◽  
Least Mean Square ◽  
Step Size ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Normalized Lms

A power generating system should be able to generate and feed quality power to the loads which are connected to it. This paper suggests a very efficient controlling technique, supported by an effective optimization method, for the control of voltage and frequency of the electrical output of an isolated wind power harnessing unit. The wind power unit is modelled using MATLAB/SIMULINK. The Leaky least mean square algorithm with a step size is used by the proposed controller. The Least Mean Square (LMS) algorithm is of adaptive type, which works on the online modification of the weights. LMS algorithm tunes the filter coefficients such that the mean square value of the error is the least. This avoids the use of a low pass filter to clean the voltage and current signals which makes the algorithm simpler. An adaptive algorithm which is generally used in signal processing is applied in power system applications and the process is further simplified by using optimization techniques. That makes the proposed method very unique. Normalized LMS algorithm suffers from drift problem. The Leaky factor is included to solve the drift in the parameters which is considered as a disadvantage in the normalized LMS algorithm. The selection of suitable values of leaky factor and the step size will help in improving the speed of convergence, reducing the steady-state error and improving the stability of the system. In this study, the leaky factor, step size and controller gains are optimized by using optimization techniques. The optimization has made the process of controller tuning very easy, which otherwise was carried out by the trial-and-error method. Different techniques were used for the optimization and on result comparison, the Antlion algorithm is found to be the most effective. The controller efficiency is tested for loads that are linear and nonlinear and for varying wind speeds. It is found that the controller is very efficient in maintaining the system parameters under normal and faulty conditions. The simulated results are validated experimentally by using dSpace 1104. The laboratory results further confirm the efficiency of the proposed controller.

Output statistics of a line enhancer based on a combination of two adaptive filters

2011 ◽  
Vol 1 (3) ◽  
Author(s):  
Trump Tõnu
Keyword(s):  
Steady State ◽  
Adaptive Filters ◽  
Wiener Filter ◽  
Small Step ◽  
Step Size ◽  
Second Order Statistics ◽  
Adaptive Combination ◽  
Small Step Size ◽  
Adaptive Line Enhancer ◽  
Affine Combination

AbstractThis paper studies output statistics of an adaptive line enhancer that is based on an affine combination of two NLMS adaptive filters. Combination of adaptive filters is a new interesting way of improving the performance of adaptive algorithms. The structure consists of two adaptive filters that adapt on the same input signal, one with a large and the other one with a small step size. Such a combination is capable of achieving fast initial convergence and small steady state error at the same time. In this paper we investigate the second order statistics of the output signal of adaptive line enhancer based on the combination in steady state. The result is given in terms of the parameters of the adaptive combination, input process statistics, and the optimal Wiener filter weights for the problem at hands.

Simulation Realization of Adaptive Filtering Based on a Normalized LMS Algorithm

2013 ◽  
Vol 373-375 ◽  
pp. 1159-1163
Author(s):  
Ya Feng Li ◽  
Zi Wei Zheng
Keyword(s):  
Adaptive Filtering ◽  
Notch Filter ◽  
Lms Algorithm ◽  
Variable Step Size ◽  
Step Size ◽  
Filtering Algorithm ◽  
Adaptive Notch Filter ◽  
Variable Step ◽  
Simulation Results ◽  
Normalized Lms

This paper presents the new algorithm which is an improved normalized variable step size LMS adaptive filtering algorithm. A normalized LMS algorithm with variable step size iterative formula is deduced and at the same time the simulation results prove that the new algorithm has good performance. The LMS adaptive filtering algorithm has been widely used in many applications such as system identification, noise cancellation and the adaptive notch filter ,the paper analyses the application and implement the simulation by matlab. the result shows the proposed algorithm has been applied well.

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