C.D. Giurcaneanu

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The paper is focused on the problem of discrete universal denoising: one estimates the input sequence to a discrete channel based on the observation of the entire output signal, and without assuming any particular knowledge on the statistical properties of the input sequence. A 2k + 1 sliding window denoiser (DUDE) has recently been introduced, and its(More)
The paper considers the problem of building genetic networks from time series of gene expression data. The class of models of interest is that of systems of differential equations specifying gene-gene interactions and the goal is to infer the network structure from experimental gene expression data. As a mean to regularize the inverse problem, we assume the(More)
The problem we address in this study is to decide, based on the available measurements, if a particular gene exhibits a periodic behavior. To this end we propose a principled method relying on the Stochastic Complexity (SC) whose computation is discussed for the generalized Gaussian distribution. We also investigate the relationship between SC, the(More)
The paper is focused on the prediction stage for lossless audio coding. We rely on the piecewise autoregressive model to design a compressor dubbed PAR for which the complexity of the decoder is low such that to be easily implemented on economic devices. The performances of the new coder are evaluated for two data sets of monaural audio signals sampled at(More)
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