Kristen Feher

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Clustering of gene expression data is often done with the latent aim of dimension reduction, by finding groups of genes that have a common response to potentially unknown stimuli. However, what is poorly understood to date is the behaviour of a low dimensional signal embedded in high dimensions. This paper introduces a multicollinear model which is based on(More)
Random matrix theory (RMT) is well suited to describing the emergent properties of systems with complex interactions amongst their constituents through their eigenvalue spectrums. Some RMT results are applied to the problem of clustering high dimensional biological data with complex dependence structure amongst the variables. It will be shown that a gene(More)
Digital quasi-impulse-shaped signals for the transmission of Nyquist-shaped raised-cosine filtered signals and partial response signals are considered. Quasi-impulse signals do not require conventionally used phase-equalized <i>x</i>/sin(<i>x</i>)-shaped aperture equalizers. A simple logic circuit reduces the pulse-width of the conventional NRZ format,(More)
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