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20032010
most citedEstimating Mutual Information

4.2k citations · 4.6k across the 9 of their papers we have counts for

collaborators

9 papers

physics.chem-ph2010★ 77 cited

Independent components in spectroscopic analysis of complex mixtures

Yulia B. Monakhova, Sergey A. Astakhov, Alexander Kraskov +1

We applied two methods of "blind" spectral decomposition (MILCA and SNICA) to quantitative and qualitative analysis of UV absorption spectra of several non-trivial mixture types. B…

q-bio.QM2008★ 2 cited

MIC: Mutual Information based hierarchical Clustering

Alexander Kraskov, Peter Grassberger

Clustering is a concept used in a huge variety of applications. We review a conceptually very simple algorithm for hierarchical clustering called in the following the {\it mutual i…

physics.chem-ph2006★ 51 cited

Monte Carlo Algorithm for Least Dependent Non-Negative Mixture Decomposition

Sergey A. Astakhov, Harald Stögbauer, Alexander Kraskov +1

We propose a simulated annealing algorithm (called SNICA for "stochastic non-negative independent component analysis") for blind decomposition of linear mixtures of non-negative so…

physics.data-an2004★ 6 cited

Spectral Mixture Decomposition by Least Dependent Component Analysis

Sergey A. Astakhov, Harald Stögbauer, Alexander Kraskov +1

A recently proposed mutual information based algorithm for decomposing data into least dependent components (MILCA) is applied to spectral analysis, namely to blind recovery of con…

cond-mat.dis-nn2004★ 3 cited

Extracting Phases from Aperiodic Signals

Alexander Kraskov, Thomas Kreuz, Ralph G. Andrzejak +3

We demonstrate by means of a simple example that the arbitrariness of defining a phase from an aperiodic signal is not just an academic problem, but is more serious and fundamental…

physics.comp-ph2004★ 199 cited

Least Dependent Component Analysis Based on Mutual Information

Harald Stögbauer, Alexander Kraskov, Sergey A. Astakhov +1

We propose to use precise estimators of mutual information (MI) to find least dependent components in a linearly mixed signal. On the one hand this seems to lead to better blind so…