A. D. Mercer

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Density Estimation with Mercer Kernels

We present a new method for density estimation based on Mercer kernels. The density estimate can be understood as the density induced on a data manifold by a mixture of Gaussians fit in a feature space. As is usual, the feature space and data manifold are defined with any suitable positive-definite kernel function. We modify the standard EM algorithm for mixtures of Gaussians to infer the param...

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Reproducing kernel Hilbert spaces and Mercer theorem

We characterize the reproducing kernel Hilbert spaces whose elements are p-integrable functions in terms of the boundedness of the integral operator whose kernel is the reproducing kernel. Moreover, for p = 2 we show that the spectral decomposition of this integral operator gives a complete description of the reproducing kernel.

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The Mercer online interactive chaotic pendulum

remotely control through the Internet. Our objective is threefold. We are attempting to provide an educational resource for chaos, demonstrate a new technology, and experiment with a new method of laboratory education. Figure 1 shows the pendulum control panel. As students vary the driving frequency, they can watch the pendulum's motion switch from simple periodic motion to chaotic motion. The ...

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Mercer kernel-based clustering in feature space

The article presents a method for both the unsupervised partitioning of a sample of data and the estimation of the possible number of inherent clusters which generate the data. This work exploits the notion that performing a nonlinear data transformation into some high dimensional feature space increases the probability of the linear separability of the patterns within the transformed space and...

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Non-Mercer Kernels for SVM Object Recognition

On the one hand, Support Vector Machines have met with significant success in solving difficult pattern recognition problems with global features representation. On the other hand, local features in images have shown to be suitable representations for efficient object recognition. Therefore, it is natural to try to combine SVM approach with local features representation to gain advantages on bo...

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ژورنال

عنوان ژورنال: British Corrosion Journal

سال: 1996

ISSN: 0007-0599

DOI: 10.1179/000705996798114338