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In this paper, we investigate the nonlinear, finite dimensional and data independent random Fourier feature expansions that can approximate the popular Gaussian kernel. With recursive least squares algorithm, we develop the Random Fourier Feature Recursive Least Squares algorithm (RFF-RLS), which shows significant performance improvements in simulations when compared with several other online kernel...
Fog cover is generally present in outdoor scenes, which limits the potential for efficient information extraction from images. In this paper, the goal of the developed algorithm is to obtain an optimal transmission map as well as to remove hazes from a single input image. To solve the problem, we meticulously analyze the optical model and recast the initial transmission map under an additional boundary...
Kernel adaptive filters (KAFs) are powerful tools for online nonlinear system modeling, which are direct extensions of traditional linear adaptive filters in kernel space, with growing linear-in-the-parameters (LIP) structure. However, like most other nonlinear adaptive filters, the KAFs are “black box” models where no prior information about the unknown nonlinear system is utilized. If some prior...
Kernel least mean square is a simple and effective adaptive algorithm, but dragged by its unlimited growing network size. Many schemes have been proposed to reduce the network size, but few takes the distribution of the input data into account. Input data distribution is generally important in view of both model sparsification and generalization performance promotion. In this paper, we introduce an...
To understand emotion and make machine emotion is one of the goals of affective computing. In order to understand language from interface of machine, both the meaning and the emotion are necessary to be interpreted correctly. But until now the study of fine-grained theory of emotion is still full of challenges. In this paper, a novel method to analyze emotion category is proposed according to the...
Affective computing is attracting attentions as a popular growing field with many applications such as Kansei engineering, information retrieval and HCI. But until now the study of fine-grained theory of emotion is still a challenge. In this paper, a novel method to analyze emotion category is proposed according to the statistics of affective property in Dictionary of contemporary Chinese. These emotion...
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