This paper presents the sliding exponential window max-correlation matching (SEWMCM) adaptive algorithm and the sliding rectangular window max-correlation matching (SRWMCM) adaptive algorithm for finding the maximum c...
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This paper presents the sliding exponential window max-correlation matching (SEWMCM) adaptive algorithm and the sliding rectangular window max-correlation matching (SRWMCM) adaptive algorithm for finding the maximum correlation of two different signal vectors. A unified approach to the steady-state excess mean square error (MSE) performance analyses for proposed algorithms is developed, including several general close-form analytical expressions based on the non-stationary system identification model. It is conclusively shown by numerical simulations that the SEWMCM algorithm converges faster than the SRWMCM algorithm, whereas the estimation accuracy and the steady-state performance of the SRWMCM outperform those of the SEWMCM and the conventional exponentially-weighted RLS (EWRLS).
Uterine Electromyography (EMG) signal is often contaminated by electronic and electromagnetic noises and by the remaining electrocardiogram of the mother. Therefore, an efficient noise cancellation is essential for a ...
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ISBN:
(纸本)9781467385275
Uterine Electromyography (EMG) signal is often contaminated by electronic and electromagnetic noises and by the remaining electrocardiogram of the mother. Therefore, an efficient noise cancellation is essential for a better clinical evaluation. In recent literatures, several techniques have been adopted to reject noises from EMG recordings. In this paper, Least Mean Square (LMS) and Recursive Least Square (RLS) adaptive algorithms are proposed to denoise uterine EMG signals. Simulations were performed in MATLAB Simulink environment. The obtained results are then compared with wavelet transform and 0.34-1 HZ band-pass filter using signal to noise ratio measures. Results show that RLS based algorithm performs the best among the other tested algorithms.
We present a novel family of adaptive filtering algorithms based on a relative logarithmic cost. The new family intrinsically combines the higher and lower order measures of the error into a single continuous update b...
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ISBN:
(纸本)9781479928941
We present a novel family of adaptive filtering algorithms based on a relative logarithmic cost. The new family intrinsically combines the higher and lower order measures of the error into a single continuous update based on the error amount. We introduce the least mean logarithmic square (LMLS) algorithm that achieves comparable convergence performance with the least mean fourth (LMF) algorithm and overcomes the stability issues of the LMF algorithm. In addition, we introduce the least logarithmic absolute difference (LLAD) algorithm. The LLAD and least mean square (LMS) algorithms demonstrate similar convergence performance in impulse-free noise environments while the LLAD algorithm is robust against impulsive interference and outperforms the sign algorithm (SA).
This paper studies transfer learning for estimating the mean of random functions based on discretely sampled data, where, in addition to observations from the target distribution, auxiliary samples from similar but di...
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This paper presents speech enhancement using Generalized Sidelobe Canceller (GSC) beamforming with different adaptive algorithms to improve the quality of speech signal in a noisy environment. GSC beamforming provides...
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This paper presents speech enhancement using Generalized Sidelobe Canceller (GSC) beamforming with different adaptive algorithms to improve the quality of speech signal in a noisy environment. GSC beamforming provides spatial filtering to enhance the desired signal from various noisy environments. In this paper, GSC beamformer with Least Mean Square (LMS), Normalized LMS (NLMS) and Recursive least square (RLS) are implemented and their performance is evaluated under various noisy conditions. From the simulation results, it can be deduced that the GSC beamformer with RLS achieves better performance compared to GSC with LMS, and NLMS algorithms. The performance metrics like Signal to Noise Ratio (SNR), Perceptual Evaluation of Speech Quality (PESQ) and Log Likelihood Ratio (LLR) are used to validate our results.
The Discontinuous Galerkin time-domain method is well suited for adaptive algorithms to solve the time-domain Maxwell’s equations and depends on robust and economically computable drivers. adaptive algorithms utilize...
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COSMO-SkyMed di Seconda Generazione (COSMO-SkyMed Second Generation, CSG) is an "end-to-end" and "dual use" (Civilian and Defence) Italian Earth Observation Space System conceived at the twofold ob...
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ISBN:
(纸本)9781479979301
COSMO-SkyMed di Seconda Generazione (COSMO-SkyMed Second Generation, CSG) is an "end-to-end" and "dual use" (Civilian and Defence) Italian Earth Observation Space System conceived at the twofold objective of ensuring operational continuity to the current constellation (COSMO-SkyMed - CSK), while improving functionality and performances. CSG primary mission objective is to promptly and effectively satisfy the heterogeneous user needs (institutional, scientific and commercial purposes) producing a mission plan that satisfies the higher priority requests and optimizes the overall plan with the remaining lower priority requests according to the users programming rights consumption, while fully employing the system resources and taking into account both technical and managerial constraints. Indeed the CSG Mission Planning and Scheduling tool implements innovative adaptive planning algorithms based on both priority criteria and saturation of system resources that envisage two scheduling strategies, the rank-based and the optimization-based respectively. The CSG algorithms are implemented in an iterative dynamic process of finding optimal solutions able to better answer the demanding requirements coming from the heterogeneous users.
In this paper, we consider the problem of prediction with expert advice in dynamic environments. We choose tracking regret as the performance metric and derive novel data-dependent bounds by developing two adaptive al...
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In this paper, we address the problem of cache invalidation in mobile environments, where such system environment parameters as client disconnection times and update/query rates vary dynamically. We propose two adapti...
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In this paper, we address the problem of cache invalidation in mobile environments, where such system environment parameters as client disconnection times and update/query rates vary dynamically. We propose two adaptive caching algorithms that are the extensions of the Timestamps (TS) algorithm proposed in [4]. We implement a simulation model of a client-server system that supports mobile hosts over wireless communication channels. We use this model to compare these adaptive algorithms under conditions of changing environmental parameters. The results of this simulation provide some interesting insights into how these adaptive algorithms adjust dynamically to changing parameters. (C) Elsevier Science Inc. 1996
作者：
Gantner, GregorPraetorius, DirkUniversity of Amsterdam
Faculty of Science Korteweg-de Vries Instituut Postbus 94248 Amsterdam1090 GE Netherlands TU Wien
Institute for Analysis and Scientific Computing Wiedner Hauptstraße 8-10/E101/4 Vienna1040 Austria
We consider h-adaptive algorithms in the context of the finite element method (FEM) and the boundary element method (BEM). Under quite general assumptions on the building blocks SOLVE, ESTIMATE, MARK, and REFINE of su...
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