Removal of noises from ECG (Electrocardiogram) signal is a classical problem. Moreover, nullifying AC and DC noises using the two adaptive algorithms-the LMS and the RLS from the ECG is a new study in biomedical scien...
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Phonocardiography is a widely used procedure for understanding the functioning of human heart and diagnosing heart diseases. However, the Phonocardiogram (PCG) signals obtained during this process are susceptible to n...
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Permanent magnet synchronous motors (PMSMs) produce a parasitic oscillating torque due to several reasons. This contribution cancels the oscillating torque with adaptive control algorithms. Therefore a mathematical mo...
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We suggest a new method to design adaptation algorithms that guarantee improved performance and are applicable for a class of plants with nonconvex parameterization. The main idea of the method is, first, to augment t...
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The architecture and some basic applications of a single-chip software-programmable digital signal processor are presented. This NMOS 3.5 um silicon gate circuit is well-suited for adaptive algorithms and some input a...
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In this paper, we examine a high resolution direction of arrival (DOA) estimation techniques. Among of these algorithms which can yield accurate DOA estimates for multiple narrow band sources are Gabriel's thermal...
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In this paper, we examine a high resolution direction of arrival (DOA) estimation techniques. Among of these algorithms which can yield accurate DOA estimates for multiple narrow band sources are Gabriel's thermal noise, adaptive angular response, and maximum-likelihood method. These algorithms are capable of detecting pulse that exists for short periods of time. Under this environment, the performance of different adaptive superresolution array algorithms that utilize the Howell-Applebaum technique is compared. Two different cases are discussed. Firstly, the adaptive array is subjected to only one signal plus thermal noise. Secondly, the case of the presence of two incident signals plus thermal noise is investigated. It is shown that every algorithm offers its best performance depending upon the incident signal parameters, number of antennas, the range of input signal-to-noise ratio, and the angle of separation between the incoming signals.
In this paper we introduce an automatic gain control (AGC) scheme for adaptive algorithms that are used extensively in many applications. The proposed AGC scheme is realized by using an estimate of the cross correlati...
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In this paper, we present an adaptive algorithm for the estimation of source parameters when a release of pollutant in the atmosphere is observed by a sensor network in complex flow field. Due to the error-based obser...
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In this paper, we present an adaptive algorithm for the estimation of source parameters when a release of pollutant in the atmosphere is observed by a sensor network in complex flow field. Due to the error-based observations, inverse statistical methods have to be used to perform an estimation of the parameters (position of the source, time and mass of the release) of interest. However, given the complexity of the dispersion model, even with a Gaussian assumption on the sensor-based errors, direct inversion cannot be done. In order to have quick results, classical MCMC, while accurate, is too slow. We then demonstrate the accuracy of using adaptive techniques such as the AMIS (Population Monte-Carlo based). We finally compare the results with the classical MCMC estimation in term of accuracy and velocity of implementation.
We study a class of adaptive Markov Chain Monte Carlo (MCMC) processes which aim at behaving as an optimal- target process via a learning procedure. We show, under appropriate conditions, that the adaptive process and...
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ISBN:
(纸本)1595935045
We study a class of adaptive Markov Chain Monte Carlo (MCMC) processes which aim at behaving as an optimal- target process via a learning procedure. We show, under appropriate conditions, that the adaptive process and optimal (nonadaptive) MCMC algorithm share identical asymptotic properties. The special case of adaptive MCMC algorithms governed by stochastic approximation is considered in details and we apply our results to the adaptive Metropolis lgorithm of [1]. We also propose a new class of adaptive MCMC algorithms, called quasi-perfect adaptive MCMC which possesses appealing theoretical and practical properties, as demonstrated through numerical simulations. Copyright 2006 ACM.
The dynamics equation of robot manipulators is non linear and coupled. An inverse dynamic control algorithm that requires a full knowledge of the dynamics of the system is one way to solve the control movement. Adapti...
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