Computer Science – Information Theory
Scientific paper
2008-10-30
Computer Science
Information Theory
Sent to IEEE Transactions on Information Theory (september 2008)
Scientific paper
A new combinatorial-probabilistic diagnostic entropy has been introduced. It describes the pair-wise sum of probabilities of system conditions that have to be distinguished during the diagnosing process. The proposed measure describes the uncertainty of the system conditions, and at the same time complexity of the diagnosis problem. Treating the assumed combinatorial-diagnostic entropy as a primary notion, the information delivered by the symptoms has been defined. The relationships have been derived to facilitate explicit, quantitative assessment of the information of a single symptom as well as that of a symptoms set. It has been proved that the combinatorial-probabilistic information shows the property of additivity. The presented measures are focused on diagnosis problem, but they can be easily applied to other disciplines such as decision theory and classification.
No associations
LandOfFree
A Combinatorial-Probabilistic Diagnostic Entropy and Information does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with A Combinatorial-Probabilistic Diagnostic Entropy and Information, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A Combinatorial-Probabilistic Diagnostic Entropy and Information will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-279145