Browsing by Author "Panov, Vladimir A."
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- ItemEstimation of the signal subspace without estimation of the inverse covariance matrix(Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik, 2010) Panov, Vladimir A.Let a high-dimensional random vector $vecX$ can be represented as a sum of two components - a signal $vecS$, which belongs to some low-dimensional subspace $mathcalS$, and a noise component $vecN$. This paper presents a new approach for estimating the subspace $mathcalS$ based on the ideas of the Non-Gaussian Component Analysis. Our approach avoids the technical difficulties that usually exist in similar methods - it doesn't require neither the estimation of the inverse covariance matrix of $vecX$ nor the estimation of the covariance matrix of $vecN$.
- ItemNon-Gaussian component analysis : new ideas, new proofs, new applications(Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik, 2010) Panov, Vladimir A.In this article, we present new ideas concerning Non-Gaussian Component Analysis (NGCA). We use the structural assumption that a high-dimensional random vector $vX$ can be represented as a sum of two components