In this paper a fuzzy C-means (FCM) based approach for speech/non-speech discrimination is developed to build an effective voice activity detection (VAD) algorithm. The proposed VAD method is based on a soft-decision ...
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We present a method to cluster the information contained in 3-dimensional brain images where each cluster incorporates a contiguous brain region with similar activation. The grey-level distribution of a brain image is...
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The memory hierarchy has a high impact on the performance and power consumption in the system. Moreover, current embedded systems, included in mobile devices, are specifically designed to run multimedia applications, ...
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We present a method to cluster the information contained in 3-dimensional brain images where each cluster incorporates a contiguous brain region with similar activation. The grey-level distribution of a brain image is...
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We present a method to cluster the information contained in 3-dimensional brain images where each cluster incorporates a contiguous brain region with similar activation. The grey-level distribution of a brain image is approximated by a sum of Gaussian functions and the parameters of the Gaussian mixture are determined by a maximum likelihood criterion via the expectation maximization (EM) algorithm. Each cluster, therefore, is represented by a multivariate Gaussian function with a definite centre coordinate and a certain shape. This approach leads to a drastic compression of the information contained in the brain image and serves as a starting point for a variety of possible feature extraction methods for the diagnosis of brain diseases.
There remains an open question about the usefulness and the interpretation of Machine learning (MLE) approaches for discrimination of spatial patterns of brain images between samples or activation states. In the last ...
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