Least Mean Square
Variable, Step-Size, Block Normalized, Least Mean, Square Adaptive Filter: A Unied Framework
... The least mean square (LMS) and its normalized version (NLMS) are the workhorses of adaptive ...steady-state mean square ...steady-state Mean Square Error ...
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Power quality assessment using least mean square filter and fuzzy expert system
... endorse for investigation of signals with limited transient parts emerging in the signal examination [6, 7]. WT also shows a few weaknesses for example, its complex calculation, affectability to noise level, and the ...
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FIXED POINT LEAST MEAN SQUARE ADAPTIVE FINITE IMPULSE RESPONSE FILTER
... Fir filters is highly used in Digital communication & Signal processing applications Digital radio receivers, Downconverts Software Radio.in this project I present an efficient architecture for the implementation of ...
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NOISE CANCELLATION USING LEAST MEAN SQUARE AND WAVELET TRANSFORM FOR SPEECH ENHANCEMENT
... available. Least Mean Square (LMS) is the algorithm used to update filter coefficients by subtracting the desired signal from input signal producing error signal which updates the algorithm variables ...
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A Zero-attracting Quaternion-valued Least Mean Square Algorithm for Sparse System Identification
... Jiang, M.D., Liu, W. and Li, Y. (2014) A Zero-attracting Quaternion-valued Least Mean Square Algorithm for Sparse System Identification. In: 9th International Symposium on Communication Systems, ...
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Correction of WOW and Flutter in Audio Signals using Least Mean Square Algorithm
... using Least Mean Square ...occurs. Least Mean Square Algorithm uses Adaptive Filter which adjusts their coefficient in order to minimize the required wobble effects in audio ...
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Least Mean Square (LMS) Adaptive Line Enhancer (ALE) Design for Modern Communication
... (LMS) Least Mean Square adaptive filter is a well behaved signal processing algorithm is used in applications where a system to adapt to its ...
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Power System Frequency Estimation using Least Mean Square Filter based Algorithm
... Abstract: In the field of electrical power sector frequency as a parameter plays an important role. The value of frequency is not constant, varies according to the load conditions. The power system functionalities like ...
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Performance Improvement in Amplitude Synthesis of Unequally Spaced Array Using Least Mean Square Method
... the least mean square error technique to solve the system ofequations resulting in a better pattern synthesis and result in lower side lobe level about 5 dB in comparison with the existing Legendre ...
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LUT Optimization for scattered Arithmetic-Based Block Least Mean Square Adaptive (LMSA) Filter
... Adaptive filters are widely used in several digital signal processing applications. The most usually used adaptive filter is the tapped-delay line finite impulse response (FIR) filter whose weights are updated by the ...
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Comparative Analysis for Least Mean Square and Normalized LMS for Speech Enhancement Application
... Abstract— Adaptive Signal Processing (ASP) is an active research area. Adaptive Filter based speech enhancement technique is now a day’s getting very popular due to wide range of applications like mobile communication, ...
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Statistical Study of Least Mean Square and Normalised Least Mean Square Algorithms
... the Least-Mean Square behavior for cyclostationary inputs examined only its convergence in the ...the Least Mean Fourth (LMF) algorithm behavior for non-stationary inputs has been ...
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A Two-Stage Approach for Improving the Convergence of Least-Mean-Square Adaptive Decision-Feedback Equalizers in the Presence of Severe Narrowband Interference
... It has previously been shown that a least-mean-square (LMS) decision-feedback filter can mitigate the effect of narrowband inter- ference (L.-M. Li and L. Milstein, 1983). An adaptive implementation ...
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Automatic Multiple Face Recognition and Annotation Based on Principle Component Analysis cum Least Mean Square Error (PLMSE)
... ABSTRACT: Face recognition has received substantial attention from researchers in biometrics, pattern recognition field and computer vision communities. Major drawback in old work was that this method was design to ...
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The Design and Implementation of Notch Filter Based on Least Mean Square
... Abstract. Data acquisition and analysis system often encounters interference of single frequency or narrowband signal in work. For example, in power frequency environment, 50Hz interference signal often affects the ...
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ECG Signal Denoising by Using Least Mean Square and Normalised Least Mean Square Algorithm Based Adaptive Filter R Karthika, K Narender & Dr B R Vikram
... Electrocardiogram (ECG) is a method of measuringthe electrical activities of heart. Every portion of ECG is veryessential for the diagnosis of different cardiac problems. But theamplitude and duration of ECG signal is ...
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Applications of Least Mean Square (LMS) Algorithm Regression in Time Series Analysis
... Applications of Least Mean Square LMS Algorithm Regression in Time-Series Analysis Giovanis, Eleftherios.[r] ...
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ECG Signal Denoising by Using Least-Mean-Square Based Adaptive Filter
... with least mean square (LMS) algorithm showgood performance for process- ing and analysis of signal whichare non-stationary ...malized least mean square (NLMS)filter to denoise ...
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Encumbered Constancy Least Mean Square Algorithm for AEC’s in Mobile Communication Systems
... In AEC systems, the adaptive filter coefficients are disturbed by mainly two factors. Those are power fluctuation of far end talker's signal which can be used to estimate the coefficients. Even though, by applying the ...
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Estimation of hospital emergency room data using otc pharmaceutical sales and least mean square filters
... Here, we consider the clinical data as the primary channel of an adaptive LMS filter. The OTC product groups are then used to estimate the daily clinical data in the follow- ing manner. Today's and several past days' OTC ...
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