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Input Pattern Classification Based on the Markov Property of the IMBT with Related Equations and Contingency Tables
István Finta1, Sándor Szénási2, Lóránt Farkas1
1Nokia, Bell Labs, Bókay street 36-42, H-1083 Budapest, Hungary.
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.
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