Lucena, B and Kontoyiannis, I (2005) *Filtering: The case for "Noisier" data.* In: UNSPECIFIED pp. 128-130..

## Abstract

Suppose there is some discrete variable X of interest, which can only be observed after passing through 2 channels (Q and R). You are limited to n noisy observations of X and then must estimate the value of X. Your one control is a parameter k which determines the level of correlation in your observed data. Specifically, X is first transmitted through the channel Q n/k times to yield variables Y1,...,Yn/k, and then each Yi is transmitted through channel R k times to yield variables Zi,1,..., Zi,k. How should k be chosen to maximize the probability of successfully guessing the correct value of X? While k = 1 yields data points Zi,1 which are conditionally independent given the value of X, we find that this does not always mean that k = 1 is the optimal choice. In fact, many simple situations yield cases where the optimal value of k is greater than 1. We explore this phenomenon and present both theoretical and empirical results. © 2005 IEEE.

Item Type: | Conference or Workshop Item (UNSPECIFIED) |
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Subjects: | UNSPECIFIED |

Divisions: | Div F > Signal Processing and Communications |

Depositing User: | Cron Job |

Date Deposited: | 08 Jan 2018 20:12 |

Last Modified: | 18 Aug 2020 12:42 |

DOI: | 10.1109/ITW.2005.1531872 |