Estimating the amplitude and phase of a signal accurately even when the frequencies contained in the signal are already known is very important in many areas. The estimation accuracy and the estimation time are import...
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Estimating the amplitude and phase of a signal accurately even when the frequencies contained in the signal are already known is very important in many areas. The estimation accuracy and the estimation time are important issues in such areas and a method of improving both of these issues by combining the notch characteristics and the band passing characteristics of serially connected notch filters and an adaptive algorithm is presented in this paper. Computer simulations reveal that the performance of the proposed method is superior to previously proposed methods. (C) 2001 Scripta Technica, Electron Comm Jpn Pt 3, 85(2): 65-73,2002.
Active vibration control in AC machines is used for minimizing the radial rotor vibrations. These vibrations are caused by structural characteristics of the machine and they occur in all kinds of electrical machines. ...
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Active vibration control in AC machines is used for minimizing the radial rotor vibrations. These vibrations are caused by structural characteristics of the machine and they occur in all kinds of electrical machines. Several active control methods have been applied in the machines and the results have been promising. This paper introduces two new methods that utilize the theory of linear time periodic systems. The first method gives a periodic feedback control as a solution to a discrete-time periodic Riccati equation (DPRE). The second method yields a feedforward type controller that is capable of compensating several simultaneous disturbance signals of different frequencies summed to the output of the system. It is possible to use these two control methods such that they form a serial control topology algorithm.
The coefficient reuse strategy is able to improve the steady-state performance of adaptive filter algo-rithms, especially in very challenging low signal-to-noise scenarios. This paper advances deterministic and stocha...
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The coefficient reuse strategy is able to improve the steady-state performance of adaptive filter algo-rithms, especially in very challenging low signal-to-noise scenarios. This paper advances deterministic and stochastic models that predict various learning characteristics of the lms algorithm with coefficient reuse. First-order and second-order analyzes are derived for the sufficient order case and then extended for the tracking and deficient length scenarios. An exact expectation analysis, which does not employ the ubiquitous independence assumption, is presented for a particular configuration of the algorithm, and its results suggest that, except in the first phase of the learning process, the decay in mean-square deviation of the coefficient vector is governed by an almost-sure theoretical analysis. The simulation results confirm the equations obtained in the theoretical analysis. (c) 2022 Elsevier B.V. All rights reserved.
In this paper, we propose a new adaptive filter and adaptive nonlinear predictor to implement the nonlinear prediction of speech signals to solve the problem of impulse-shaped residual errors in the linear prediction....
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In this paper, we propose a new adaptive filter and adaptive nonlinear predictor to implement the nonlinear prediction of speech signals to solve the problem of impulse-shaped residual errors in the linear prediction. While using order statistics processing, we add an improvement that keeps time information about the input signal to the lms-L filter proposed by Pitas and Venetsanopoulos. Tests using synthesized speech show that the proposed nonlinear predictor has superior, prediction performance to the Volterra series predictor and not just the linear predictor. However, even with this proposed nonlinear predictor, the prediction accuracy degrades in experiments using real speech. Therefore, we propose a new iterative method to conquer this problem. The iterative method pays attention to the periodicity of the speech, reuses the speech data, and obtains a prediction accuracy similar to when using many data samples. In experiments on real continuous speech, the proposed predictor improved prediction accuracy by using the iterative method, and the effectiveness of the method was confirmed. (c) 2005 Wiley Periodicals, Inc.
In order for a piezoelectric transducer to be used as asensor and actuator simultaneously, a direct charge due to the applied voltage must be removed from the total response in order to allow observation of the mechan...
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In order for a piezoelectric transducer to be used as a
sensor and actuator simultaneously, a direct charge due to
the applied voltage must be removed from the total response
in order to allow observation of the mechanical response
alone. Earlier researchers proposed electronic
compensators to remove this term by creating a reference
signal which destructively interferes with the direct
piezoelectric charge output, leaving only the charge
related to the mechanical response signal. This research
presents alternative analog lms adaptive filtering methods
which accomplish the same result. The main advantage of
the proposed analog compensation scheme is its ability to
more closely match the order of the adaptive filter to the
assumed dynamics of the piezostructure using an adaptive
first-order high-pass filter. Theoretical and experimental
results are provided along with a discussion of the
difficulties encountered in trying to achieve perfect
compensation of the feedthrough capacitive charge on a
piezoelectric wafer.
This paper analyzes the effect of a processing delay on the Least Mean Squares (lms) algorithm for a system identification problem when the processing delay is in the adaptive arm of the filter. Thus the sensing of th...
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This paper analyzes the effect of a processing delay on the Least Mean Squares (lms) algorithm for a system identification problem when the processing delay is in the adaptive arm of the filter. Thus the sensing of the input signal is delayed. The input is assumed to be a zero mean stationary Gaussian process. The theoretical mean and mean square behavior of the adaptive weight vector is analyzed. The weight vector is shown to be biased and significantly affects the mean square deviation (MSD). Monte Carlo simulations are presented in support of the assumptions used to derive the theoretical model as a function of the delay, bandwidth and step-size for the lms algorithm. The results suggest bias problems with other more complicated adaptive filtering algorithms such as Normalized lms and Recursive Least Squares.
The Volterra filter is one of the digital filters that can describe nonlinearity. In this paper, we analyze the dynamic behaviors of an adaptive signal processing system with the Volterra filter for nonwhite input sig...
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The Volterra filter is one of the digital filters that can describe nonlinearity. In this paper, we analyze the dynamic behaviors of an adaptive signal processing system with the Volterra filter for nonwhite input signals by a statistical -mechanical method. Assuming the self -averaging property with an infinitely long tapped -delay line, we derive simultaneous differential equations that describe the behaviors of macroscopic variables in a deterministic and closed form. We analytically solve the derived equations to reveal the effect of the nonwhiteness of the input signal on the adaptation process. The results for the second -order Volterra filter show that the nonwhiteness decreases the mean -square error (MSE) in the early stages of the adaptation process and increases the MSE in the later stages.
Hlavním cílem této bakalářské práce je popsat adaptivní číslicovou filtraci a zároveň popsat různé druhy adaptačních algoritmů a adaptivních filtrů. Adaptiv...
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Hlavním cílem této bakalářské práce je popsat adaptivní číslicovou filtraci a zároveň popsat různé druhy adaptačních algoritmů a adaptivních filtrů. Adaptivní systém je použit pro odstranění síťového rušení ze signálu EKG. Práce obsahuje návrh 4 druhů adaptivních filtrů: prostého adaptivního filtru, jednoduché úzkopásmové adaptivní zádrže, úzkopásmové adaptivní zádrže s číslicovým rezonátorem a úzkopásmové zádrže s adaptivním rezonátorem. Také obsahuje základní experimenty s různým nastavením jejich parametrů, které jsou také vyhodnoceny.
An active noise control (ANC) system utilizing a genetic algorithm for reduction of noise in duct is described. A continuous genetic algorithm with a heuristic crossover method was applied in the controller of the sys...
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An active noise control (ANC) system utilizing a genetic algorithm for reduction of noise in duct is described. A continuous genetic algorithm with a heuristic crossover method was applied in the controller of the system. The ANC system was tested on a laboratory stand. Measurements of the efficiency of the system related to basic parameters of the genetic algorithm were performed. A comparison of the effectiveness of ANC system based on the genetic algorithm to the system based on the lms algorithm is presented.
In this letter, a new rapid converging method based on orthogonalization is proposed. Our approach is to find the near-optimum coefficient values during training period, and then use them as the initial values of the ...
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In this letter, a new rapid converging method based on orthogonalization is proposed. Our approach is to find the near-optimum coefficient values during training period, and then use them as the initial values of the lms algorithm. The numerical results show that the rapid convergence speed of the proposed scheme does not depend on the eigenvalue spread.
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