Results 221 to 230 of about 4,690,072 (303)
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A family of logarithmic hyperbolic cosine spline nonlinear adaptive filters
Applied Acoustics, 2021Spline nonlinear adaptive filters are well known for their ability to efficiently model nonlinear systems while having low computational complexity. However, the performance of traditional spline adaptive filter degrades in the presence of impulsive ...
Vinal Patel +2 more
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International Journal of Adaptive Control and Signal Processing, 2021
The trajectory tracking control problem for a class of nonlinear systems with uncertain parameters is considered in this article. A new adaptive finite‐time tracking control is designed based on the adaptive backstepping method via the command filters ...
Jiling Ding, Weihai Zhang
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The trajectory tracking control problem for a class of nonlinear systems with uncertain parameters is considered in this article. A new adaptive finite‐time tracking control is designed based on the adaptive backstepping method via the command filters ...
Jiling Ding, Weihai Zhang
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Fractional-Order Correntropy Adaptive Filters for Distributed Processing of $\alpha$-Stable Signals
IEEE Signal Processing Letters, 2020This work revisits the problem of distributed adaptive filtering in multi-agent sensor networks. In contrast to classical approaches, the formulation relaxes the Gaussian assumption on the signal and noise to the generalized setting of $\alpha$-stable ...
V. C. Gogineni +3 more
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Nonlinear acoustic echo cancellation with kernelized adaptive filters
, 2020A well-known problem in speech communication is the occurrence of acoustic echo in hands-free telephony. There are several classical adaptive filters that have been used as a stand alone approach for linear acoustic echo cancellation(AEC).
Sanjana Sankar +5 more
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Operational Research Quarterly (1970-1977), 1976
The adaptive filtering technique has recently been proposed as a method for short-to medium-term forecasting. The present note demonstrates some of the shortcomings implicit in the theory and gives illustrative examples.
Golder, E. R., Settle, J. G.
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The adaptive filtering technique has recently been proposed as a method for short-to medium-term forecasting. The present note demonstrates some of the shortcomings implicit in the theory and gives illustrative examples.
Golder, E. R., Settle, J. G.
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1993 IEEE International Symposium on Circuits and Systems, 2002
The application of the conjugate gradient (CG) method for the identification of bilinear systems is investigated. An algorithm based on the CG method is developed for adaptive-bilinear digital filtering. This algorithm outperforms the least mean square (LMS) and recursive least squares (RLS) methods in terms of speed of convergence.
T. Bose, M.-Q. Chen
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The application of the conjugate gradient (CG) method for the identification of bilinear systems is investigated. An algorithm based on the CG method is developed for adaptive-bilinear digital filtering. This algorithm outperforms the least mean square (LMS) and recursive least squares (RLS) methods in terms of speed of convergence.
T. Bose, M.-Q. Chen
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Adaptive Kalman filters for nonlinear finite element model updating
, 2020This paper presents two adaptive Kalman filters (KFs) for nonlinear model updating where, in addition to nonlinear model parameters, the covariance matrix of measurement noise is estimated recursively in a near online manner.
Mingming Song +4 more
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Digital Signal Processing in Audio and Acoustical Engineering, 2019
Douglas L. Jones
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Douglas L. Jones
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Analysis of Distributed Adaptive Filters Based on Diffusion Strategies Over Sensor Networks
IEEE Transactions on Automatic Control, 2018In this paper, we will analyze a basic class of diffusion adaptive filters based on least mean squares algorithms. Both stability and performance analyses will be carried out under a general cooperative information condition, without such stringent ...
Siyu Xie, Lei Guo
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Visual Tracking via Adaptive Spatially-Regularized Correlation Filters
Computer Vision and Pattern Recognition, 2019In this work, we propose a novel adaptive spatially-regularized correlation filters (ASRCF) model to simultaneously optimize the filter coefficients and the spatial regularization weight.
Kenan Dai +4 more
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