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This paper studies an enhanced robust kernel least mean square (KLMS) adaptive filtering algorithm for nonlinear acoustic echo cancellation (NLAEC) in impulsive noise environment. Robust KLMS algorithm based on M-estimate theory shows robustness to simulated, Contaminated Gaussian (CG) impulsive noise. However, it fails to combat real-world impulsive noise which normally consists of a few consecutive...
It was very important for geophysical exploration to study the electromagnetic wave transient propagation characteristic in the lossy medium. A method for computing the electromagnetic wave transient propagation characteristic in layered medium based on the finite element simulation software COMSOL multi-physics was studied and the absorbing boundary condition and numerical stability condition were...
Aggregation modelling of wind farm includes equivalence of wind turbines and simplification of the collector system. Collector network is a significant part of the wind farm. Equivalent method of collector system is very important to the quality and the effectiveness of equivalent model for wind farms. As such, two different equivalent methods of collector system are studied. They are voltage-based...
This paper studies a new switch variable order affine projection algorithm (APA) for acoustic echo cancellation (AEC). Based on voice activity detection technique, a threshold calculated from the short-time energy of the far-end speech signal is derived to enable the APA to switch between the high- and low- order status. Algorithm convergence can thus be achieved when there is more input excitation...
The parameters plays an important role to the performance of support vector regression(SVR). In order to solve the problem of the Parameter optimization for SVR, first, we transform the problem of Parameter optimization into a problem of nonlinear system state estimation, then, we propose a novel algorithm based on Dual Recursive Variational Bayesian Adaptive Square-Cubature Kalman Filter (DRVB-ASCKF),...
Towards the problem of low rate of partial discharge (PD) recognition caused by lack of effective train samples, Fisher discriminant method is applied to improve recognition rate of PD for transformer. The discharge data produced by four PD models is collected, from which forty-four statistical characteristics are extracted. In order to solve the problem of singular matrix due to the high dimension,...
Fingerprint segmentation is the key step of fingerprint image preprocessing. Efficient fingerprint segmentation technology has significance in both saving preprocessing time and improving the image quality. In this paper, on the basis of the right direction of the fingerprint ridge, we use the gradient threshold method to segment image for the first time. While there are still limitations on the performance...
Traditional classification algorithms often perform well when training and testing data are drawn from the identical distribution. However, in real applications, this condition may be not satisfied. Domain adaptation is an effective approach to deal with this problem. In this paper, we propose an efficient two-stage algorithm for domain adaptation. In the label transfer stage, we utilize training...
This paper proposes a detection approach for localizing the object of specific category in images. Based on the ensemble of exemplars, a per-exemplar classifier for each exemplar is learnt, which is simple but powerful to perform well in detecting visually similar objects. Meanwhile, considering the fact that the number of negatives is always considerably larger than that of positives, the method...
This paper proposes a matching algorithm based on Delaunay Triangulation for accurate matching between affined images. This method is suitable for images rotated, scaled, translated and affined. During the matching process, triangle nets based on Delaunay theory are constructed from feature points extracted from the images. We try to find geometric invariants from the triangle nets when the images...
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