LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles.
Sign Up to like articles & get recommendations!
A New Method of Creating Minimal-Order Markov Set and Transition States of M/N Sliding Window
Photo from wikipedia
$M/N$ sliding window detection is the most commonly used method in secondary decision systems, of which the method seems simple, yet evaluating the probability of the existence of the target… Click to show full abstract
$M/N$ sliding window detection is the most commonly used method in secondary decision systems, of which the method seems simple, yet evaluating the probability of the existence of the target after several scans is rather complex. As the minimal-order Markov set is needed in the process of computation, through the analysis of equivalence of states, several conclusions of the minimal-order Markov set for $M/N$ sliding window can be derived, and then the methods for judging whether a state is a smallest equivalent state and hence, converting a state to the smallest equivalent state can be determined. Based on these conclusions, a new method that can directly create the minimal-order Markov set has been proposed, which, compared with the existing method, can greatly improve the computational efficiency of the creation. In this paper, a new method which is easier to implement and has low time complexity for calculating transition states within the minimal-order Markov set is also proposed.
