An Efficient Gaussian Mixture Reduction to Two Components
نویسندگان
چکیده
In statistical methods, such as statistical static timing analysis, Gaussian mixture model (GMM) is a useful tool for representing a non-Gaussian distribution and handling correlation easily. In order to repeat various statistical operations such as summation and maximum for GMMs efficiently, the number of components should be restricted around two. In this paper, we propose a method for reducing the number of components of a given GMM to two (2-GMM) such that the mean and the variance of the 2-GMM are equal to those of original GMM and the normalized integral square error of 2-GMM PDF is minimized. In order to demonstrate the performance of the proposed methods, we show some experimental results.
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