Displaying similar documents to “Knowledge-based Green's kernel for support vector regression.”

Application of the adaptive center-weighted vector median framework for the enhancement of cDNA microarray images

Rastislav Lukac, Bogdan Smołka (2003)

International Journal of Applied Mathematics and Computer Science

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In this paper a novel method of noise reduction in color images is presented. The new technique is capable of attenuating both impulsive and Gaussian noise, while preserving and even enhancing the sharpness of the image edges. Extensive simulations reveal that the new method outperforms significantly the standard techniques widely used in multivariate signal processing. In this work we apply the new noise reduction method for the enhancement of the images of the so called gene chips....

Accent Recognition for Noisy Audio Signals

Ma, Zichen, Fokoue, Ernest (2014)

Serdica Journal of Computing

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It is well established that accent recognition can be as accurate as up to 95% when the signals are noise-free, using feature extraction techniques such as mel-frequency cepstral coefficients and binary classifiers such as discriminant analysis, support vector machine and k-nearest neighbors. In this paper, we demonstrate that the predictive performance can be reduced by as much as 15% when the signals are noisy. Specifically, in this paper we perturb the signals with different levels...

Nonlinear image processing and filtering: A unified approach based on vertically weighted regression

Ewaryst Rafajłowicz, Mirosław Pawlak, Angsar Steland (2008)

International Journal of Applied Mathematics and Computer Science

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A class of nonparametric smoothing kernel methods for image processing and filtering that possess edge-preserving properties is examined. The proposed approach is a nonlinearly modified version of the classical nonparametric regression estimates utilizing the concept of vertical weighting. The method unifies a number of known nonlinear image filtering and denoising algorithms such as bilateral and steering kernel filters. It is shown that vertically weighted filters can be realized by...

The analysis of seasonality in economic statistics: a survey of recent developments.

Christophe Planas (1998)

Qüestiió

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This article describes the EUROSTAT activities in the field of seasonal adjustment and trend extraction in economic time series. They follow a working program which has been set up during 1995. The attention focuses on X12-REGARIMA (X12 in short), a last update of the X11-family from the Bureau of the Census (see Findley and al., 1996), and on SEATS-TRAMO (see Gomez and Maravall, 1996) which implements the ARIMA-model-based approach to decompose time series. Three main directions are...