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Synthetic aperture radar (SAR) has become one of the most powerful observation tools in the studies of natural environments and Earth resources. However the granular appearance of speckle noise in synthetic aperture radar imagery makes it very difficult to visually and automatically interpret information of SAR data. In this paper, according to the inherent speckle property of SAR image, we proposed...
The purpose of this note is to examine the performance of equity index funds in Taiwan using time-varying Jensen's and risk, which is generated by both the rolling and recursive regression approach. The empirical evidence indicates that the Taiwan Top50 Tracker Fund (TTT) is indeed characterized by relatively lower risk and better performance than the Taiwan Tracker Fund (TTF). The TTT serves as a...
Growing Asian international tourism has been significant and helpful for economic improvement in the 21st century. It is argued that the decision regarding destination choice for international tourists would be influenced by the exchange rates among origin and destination countries over time. This paper applies the panel smooth transition regression (PSTR) model to examine the asymmetric effects of...
This paper reconstructs multivariate functions from scattered data by a new multiscale technique. The reconstruction uses support vector regression model by positive definite reproducing kernels in Hilbert spaces. But it adopts techniques from wavelet theory and shift-invariant spaces to construct a new class of kernels as multiscale superpositions of shifts and scales of a single compactly supported...
Super-resolution image reconstruction has been one of the most active research areas in recent years. Based on the theory of statistical learning, Mercer condition and the wavelet frame, this paper proposes a new multiscale wavelet support vector regression model (MWSVR) to reconstruction super-resolution image from low-resolution image and missing data image. The SVM essence is kernel method and...
In this paper, we propose a robust method for the suppression of noise in medical ultrasound image by fusing the wavelet denoising technique with support vector regression (SVR). Based on the least squares support vector regression (LS- SVR), a new denoising operator and a new manipulation algorithm of wavelet coefficients are presented by incorporating neighboring coefficients. The proposed method...
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