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The maximum correntropy criterion (MCC) algorithm has attracted much attention due to its capability of combating impulsive noise. However, its performance depends on choice of the kernel width, which is a hard issue. Several variable kernel width schemes based on various error functions have been proposed to address this problem. Nevertheless, these methods may not provide an optimal kernel width because they do not contain any knowledge of the background noise that actually has influence on the optimization of the kernel width. This paper proposes an improved variable kernel width MCC algorithm, which is derived by minimizing the squared deviation at each iteration. We also design a reset mechanism for the proposed algorithm to improve its tracking capability when the estimated vector encounters a sudden change. Simulations for system identification and echo cancellation scenarios show that the proposed scheme outperforms other variable kernel width algorithms.

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To further improve the performance of the variable step size continuous mixed p-norm (VSS-CMPN) adaptive filtering algorithm in the presence of impulsive noise, a generalized VSS-CMPN algorithm (GVSS-CMPN) is proposed in this paper. Instead of assuming the probability density-like function () p λ to be uniform, a linear function is proposed for () p λ to control the mixture of various error norms. The influence of the selection of the regulating factor (slope of the linear function) is discussed. Besides, the computational complexity as well as the mean-square convergence analysis is presented. Simulations conducted in the system identification scenario demonstrate the superiority of the proposed algorithm over known algorithms.

ObjectiveTo compare the iterative decomposition of water and fat with echo asymmetry and the least-squares estimation (IDEAL) method with a fat-saturated T2-weighted (T2W) fast recovery fast spin-echo (FRFSE) imaging of the spine.Materials and MethodsImages acquired at 3.0 Tesla (T) in 35 patients with different spine lesions using fat-saturated T2W FRFSE imaging were compared with T2W IDEAL FRFSE images. Signal-to-noise ratio (SNR)-efficiencies measurements were made in the vertebral bodies and spinal cord in the mid-sagittal plane or nearest to the mid-sagittal plane. Images were scored with the consensus of two experienced radiologists on a four-point grading scale for fat suppression and overall image quality. Statistical analysis of SNR-efficiency, fat suppression and image quality scores was performed with a paired Student's t test and Wilcoxon's signed rank test.ResultsSignal-to-noise ratio-efficiency for both vertebral body and spinal cord was higher with T2W IDEAL FRFSE imaging (p < 0.05) than with T2W FRFSE imaging. T2W IDEAL FRFSE demonstrated superior fat suppression (p < 0.01) and image quality (p < 0.01) compared to fat-saturated T2W FRFSE.ConclusionAs compared with fat-saturated T2W FRFSE, IDEAL can provide a higher image quality, higher SNR-efficiency, and consistent, robust and uniform fat suppression. T2W IDEAL FRFSE is a promising technique for MR imaging of the spine at 3.0T.