least mean square (LMS)
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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Comparative Analysis for Least Mean Square and Normalized LMS for Speech Enhancement Application
... the Least - Mean – Square (LMS) algorithm, based on a gradient optimization for determining the coefficients and the class of Recursive Least-Squares algorithms ...produce least ...
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A Zero-attracting Quaternion-valued Least Mean Square Algorithm for Sparse System Identification
... In adaptive filtering [1], there is a class of algorithms specifically designed for sparse system identification, where the unknown system only has a few large coefficients while the remaining ones have a very small ...
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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
... 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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NOISE CANCELLATION USING LEAST MEAN SQUARE AND WAVELET TRANSFORM FOR SPEECH ENHANCEMENT
... the least mean square(LMS), the recursive least square (RLS) algorithm, and so on, may degenerate significantly, if the signal frequencies given to the analyzers are different from the ...
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FIXED POINT LEAST MEAN SQUARE ADAPTIVE FINITE IMPULSE RESPONSE FILTER
... the least mean squares of the error signalThe least mean square (LMS) adaptive filter is the most popular and most widely used this one so not only because of its simplicity but also ...
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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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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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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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Correction of WOW and Flutter in Audio Signals using Least Mean Square Algorithm
... use least mean square algorithm ...of least mean square algorithm such as in echo cancellation, channel equalization and teleconferencing ...
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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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Least Mean Square (LMS) Adaptive Line Enhancer (ALE) Design for Modern Communication
... The (LMS) least mean square algorithm is the simple, most powerful and famous adaptive algorithms which can be applied easily in real-time. The LMS algorithm which was developed by Widrow, trains its ...
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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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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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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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Performance Improvement in Amplitude Synthesis of Unequally Spaced Array Using Least Mean Square Method
... Abstract—In this paper, an efficient method to obtain the elements current distribution for a non uniformly spaced array is presented. For a given far field pattern, after sampling the array factor the proposed method uses ...
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Estimation of hospital emergency room data using otc pharmaceutical sales and least mean square filters
... the clinical data itself, if they exist in sufficient amounts, could be used to (self) "predict" the clinical data. If both types of predictions can be made reasonably successfully, then one could compare them ...
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Artifact Elimination in EEG Signal using Block and Sign Based Normalized Least Mean Square Techniques
... Our outcome shows that the visualized ANE’s gives the better results at clinical practices, for this we have taken the number of EEG recordings and compared them with the past experiences which have the noisy components ...
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Improved least mean square algorithm with application to adaptive sparse channel estimation
... channel estimation methods have a common drawback of sensitivity to the scaling of random training signal. Thus, it is very hard to choose a proper learning rate to achieve a robust estimation performance. To solve this ...
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Least Mean Square (LMS) for Smart Antenna
... A smart antenna system are capable of efficiently utilizing the radio spectrum and is a promise for an effective solution to the present wireless systems problems while achieving reliable and robust high speed high data ...
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