Subspace estimation plays an important role in a variety of modern signal processing applications. In an unknown and possibly changing environment, adaptive algorithms which are computationally efficient, numerically ...
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Echo interference problem widely exists in various communication channels, which seriously affects the quality of communication. In this paper four adaptive interference cancellation algorithms including LMS, Sign-LMS...
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Asymptotic optimal (AO) algorithms for detection of signals in additive autoregressive noise of order m (m-dependent Markov noise) are synthesized. The algorithms require the storage of m past data samples to achieve ...
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Asymptotic optimal (AO) algorithms for detection of signals in additive autoregressive noise of order m (m-dependent Markov noise) are synthesized. The algorithms require the storage of m past data samples to achieve optimum performance. It is AO memory discrete-time detector of a deterministic or quasideterministic signal in autoregressive noise. To assure the change of the detector's parameters as a result of learning the AO algorithm was modified to adaptive one. Combining AO algorithm with adaptation it is a powerful approach to overcome a priori uncertainty in information systems. The investigations are carried out by common approach with many simulation results.
This paper presents proofs and data for adaptive step size algorithms for tracking time-varying parameters when recursive stochastic approximation type algorithms are used. The proofs are based on recent results in st...
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This paper presents proofs and data for adaptive step size algorithms for tracking time-varying parameters when recursive stochastic approximation type algorithms are used. The proofs are based on recent results in stochastic approximation. The adaptive size technique is shown to work very well. Much supporting analysis is presented, particularly concerning the interpretation of certain stationary processes as 'stationary' pathwise derivatives. Mathematically simpler finite difference forms are also treated. These can be applied to a wide variety of systems, even when the system is not well modeled.
Several problems in signal processing can be approached as recursive identification problems for AR, ARMA or ARMAX models. The output error with extended estimation model adaptive algorithm is proposed and evaluated f...
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In this work we propose a novel asynchronous algorithm to solve the problem of optimal estimating the position of each agent in a network from relative noisy vectorial distances with its neighbours. This algorithm is ...
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The performance of some adaptive algorithms for coefficient updating of a digital echo canceller are compared. The examined algorithms are the least mean square one (LMS), the normalized LMS and the simplified version...
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A globally adaptive algorithm for approximating one-dimensional definite integrals on parallel computers is described. The algorithm is implemented on a Kendall Square Research KSR-1 parallel computer and numerical re...
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We present simple methods to enhance a recently proposed class of fully-adaptive algorithms for fault-tolerant wormhole routing. These algorithms are based on Duato's theory and are being used in several research ...
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We present simple methods to enhance a recently proposed class of fully-adaptive algorithms for fault-tolerant wormhole routing. These algorithms are based on Duato's theory and are being used in several research projects. We show that with three virtual channels per physical channel, multiple rectangular shaped fault blocks can be tolerated in two-dimensional meshes. There is no restriction on the number of faults, and maintaining fault information locally is sufficient. The logic for fault-tolerant routing is used only in the presence of faults, and there is no performance degradation in the absence of faults. The proposed technique incorporates fault-tolerance into wormhole algorithms with simple logic and low virtual channel requirements.
Variable Step-size LMS algorithms (VS LMS) have been widely applied to the inverse modeling of an unknown plant in linear adaptive inverse control system due to their advantages over standard LMS in reducing the trade...
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