1. Input Pattern Classification Based on the Markov Property of the IMBT with Related Equations and Contingency Tables
- Author
-
Istvan Finta, Lorant Farkas, and Sandor Szenasi
- Subjects
Fibonacci number ,Computer science ,General Physics and Astronomy ,Markov property ,lcsh:Astrophysics ,Interval (mathematics) ,data structure ,030226 pharmacology & pharmacy ,Article ,03 medical and health sciences ,0302 clinical medicine ,lcsh:QB460-466 ,State space ,Bernstein theorem, Fibonacci sequence ,lcsh:Science ,balanced binary tree ,Contingency table ,Binary tree ,contingency table ,state space ,Function (mathematics) ,Data structure ,lcsh:QC1-999 ,bipartite graph ,lcsh:Q ,Algorithm ,lcsh:Physics - Abstract
In this contribution, we provide a detailed analysis of the search operation for the Interval Merging Binary Tree (IMBT), an efficient data structure proposed earlier to handle typical anomalies in the transmission of data packets. A framework is provided to decide under which conditions IMBT outperforms other data structures typically used in the field, as a function of the statistical characteristics of the commonly occurring anomalies in the arrival of data packets. We use in the modeling Bernstein theorem, Markov property, Fibonacci sequences, bipartite multi-graphs, and contingency tables.
- Published
- 2020