A transition probability matrix is associated with an graph (X, T), and the classification of states in the homogenons Markov chain defined by this transition probability matrix is applied to a graph theory. Several sets of necessary and sufficient conditions for a graph to have a Hamiltonian circuit are obtained by means of the classification of these states
A Hamilton cycle in a graph is a cycle that passes through every vertex of the graph. A graph is cal...
We study graph theory. A graph is composed by a vertex set and an edge set, and each edge joins an u...
We introduce generalized quantum Markov states and generalized d-Markov chains which extend the noti...
A transition probability matrix is associated with an graph (X, T), and the classification of states...
In this paper, we present some algebraic properties of a particular class of probability transition ...
Given a directed graph and a given starting node, the Hamiltonian Cycle Problem (HCP) is to find a p...
This paper presents different methods for computing the k-transition probability matrix pk for small...
This manuscript summarizes a line of research that maps certain classical problems of discrete mathe...
This manuscript summarizes a line of research that maps certain classi-cal problems of discrete math...
ABSTRACT: We consider the Hamiltonian cycle problem embedded in singularly perturbed (con-trolled)Ma...
Graphical Models have various applications in science and engineering which include physics, bioinfo...
We consider the Hamiltonian cycle problem (HCP) embedded in a controlled Markov decision process. In...
We consider the Hamiltonian cycle problem (HCP) embedded in a controlled Markov decision process. In...
AbstractIn this paper, we derive some results giving sufficient conditions for a graph G containing ...
For an arbitrary undirected graph G, we are designing a logical model for the Hamiltonian Cycle Prob...
A Hamilton cycle in a graph is a cycle that passes through every vertex of the graph. A graph is cal...
We study graph theory. A graph is composed by a vertex set and an edge set, and each edge joins an u...
We introduce generalized quantum Markov states and generalized d-Markov chains which extend the noti...
A transition probability matrix is associated with an graph (X, T), and the classification of states...
In this paper, we present some algebraic properties of a particular class of probability transition ...
Given a directed graph and a given starting node, the Hamiltonian Cycle Problem (HCP) is to find a p...
This paper presents different methods for computing the k-transition probability matrix pk for small...
This manuscript summarizes a line of research that maps certain classical problems of discrete mathe...
This manuscript summarizes a line of research that maps certain classi-cal problems of discrete math...
ABSTRACT: We consider the Hamiltonian cycle problem embedded in singularly perturbed (con-trolled)Ma...
Graphical Models have various applications in science and engineering which include physics, bioinfo...
We consider the Hamiltonian cycle problem (HCP) embedded in a controlled Markov decision process. In...
We consider the Hamiltonian cycle problem (HCP) embedded in a controlled Markov decision process. In...
AbstractIn this paper, we derive some results giving sufficient conditions for a graph G containing ...
For an arbitrary undirected graph G, we are designing a logical model for the Hamiltonian Cycle Prob...
A Hamilton cycle in a graph is a cycle that passes through every vertex of the graph. A graph is cal...
We study graph theory. A graph is composed by a vertex set and an edge set, and each edge joins an u...
We introduce generalized quantum Markov states and generalized d-Markov chains which extend the noti...
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