Computer Science – Information Theory
Scientific paper
2011-08-04
D. Baron, "Information complexity and estimation," in Fourth Workshop Inf. Theoretic Methods Science Eng. (WITMSE 2011), Helsi
Computer Science
Information Theory
Appears at WITMSE 2011, The Fourth Workshop on Information Theoretic Methods in Science and Engineering, 7-10 August 2011, Hel
Scientific paper
We consider an input $x$ generated by an unknown stationary ergodic source $X$ that enters a signal processing system $J$, resulting in $w=J(x)$. We observe $w$ through a noisy channel, $y=z(w)$; our goal is to estimate x from $y$, $J$, and knowledge of $f_{Y|W}$. This is universal estimation, because $f_X$ is unknown. We provide a formulation that describes a trade-off between information complexity and noise. Initial theoretical, algorithmic, and experimental evidence is presented in support of our approach.
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