Estimation Theoretic
Mostrando 1-4 de 4 artigos, teses e dissertações.
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1. Information geometric similarity measurement for near-random stochastic processes
We outline the information-theoretic differential geometry of gamma distributions, which contain exponential distributions as a special case, and log-gamma distributions. Our arguments support the opinion that these distributions have a natural role in representing departures from randomness, uniformity, and Gaussian behavior in stochastic processes. We show
Publicado em: 2011
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2. Métodos híbridos para reconstrução tomográfica de imagens usando POCS e teoria da estimação / Hybrid methods for tomographic image reconstruction using POCs and estimation theory
Nesta tese é apresentado um novo método de reconstrução de imagens, por tomografia de transmissão, de projeções sujeitas a ruído na contagem de fótons. O método de reconstrução selecionado utiliza a técnica POCS (Projections Onto Convex Sets). A estimação das projeções originais a partir das observações ruidosas se dá por meio de quatro m
Publicado em: 2007
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3. The simultaneous estimation of the number of signals and frequencies of multiple sinusoids when some observations are missing: I. Asymptotics
The problem of simultaneous estimation of the number of signals and frequencies of multiple sinusoids is considered in the case when some observations are missing. The number of signals is estimated with an information theoretic criterion, and the frequencies are estimated with eigenvariation linear prediction. The strong consistency of the estimates of the
The National Academy of Sciences.
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4. MIST: Maximum Information Spanning Trees for dimension reduction of biological data sets
Motivation: The study of complex biological relationships is aided by large and high-dimensional data sets whose analysis often involves dimension reduction to highlight representative or informative directions of variation. In principle, information theory provides a general framework for quantifying complex statistical relationships for dimension reduction
Oxford University Press.