Detection, decision, and missing information

Amnon Meisels

doi:10.1016/0020-0255(85)90007-6

Detection, decision, and missing information

Amnon Meisels

Ben-Gurion University of the Negev

Research output: Contribution to journal › Article › peer-review

Abstract

A new, objective approach for optimal decision regarding signal detection is constructed. Deciding whether some data point is a signal changes the amount of missing information in the data via a feedback mechanism. By minimizing the amount of missing information in the objects one is interested in, one arrives at the optimal decision. This optimal decision is dictated by the data, in fact by the noise, or "background." In a computer experiment, with Gaussian noise, the scheme works. A minimum for the missing information exists, and an optimal decision can be made. A connection between the present approach and entropy on fuzzy sets is shown.

Original language	English
Pages (from-to)	95-106
Number of pages	12
Journal	Information Sciences
Volume	37
Issue number	1-3
DOIs	https://doi.org/10.1016/0020-0255(85)90007-6
State	Published - Dec 1985
Externally published	Yes

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10.1016/0020-0255(85)90007-6

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AB - A new, objective approach for optimal decision regarding signal detection is constructed. Deciding whether some data point is a signal changes the amount of missing information in the data via a feedback mechanism. By minimizing the amount of missing information in the objects one is interested in, one arrives at the optimal decision. This optimal decision is dictated by the data, in fact by the noise, or "background." In a computer experiment, with Gaussian noise, the scheme works. A minimum for the missing information exists, and an optimal decision can be made. A connection between the present approach and entropy on fuzzy sets is shown.

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Detection, decision, and missing information

Abstract

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