The graph entropies inspired by Shannon’s entropy concept become the information-theoretic quantities for measuring the structural information of graphs and complex networks. In this paper, we continue studying some new properties of the graph entropies based on information functionals involving vertex degrees. We prove the monotonicity of the graph entropies with respect to the power exponent. Considering only the maximum and minimum degrees of the ( n , m ) -graph, we obtain some upper and lower bounds for the degree-based graph entropy. These bounds have different performances to restrict the degree-based graph e...
The aim of this report to solve the open problem suggested by Chen et al. We study the graph entropy...
In this paper we derive entropy bounds for hierarchical networks. More precisely, starting from a re...
For measuring the complexity of a graph, an information-theoretic quantity, that is, entropy functio...
The graph entropies inspired by Shannon’s entropy concept become the information-theoretic quantitie...
Inspired by the generalized entropies for graphs, a class of generalized degree-based graph entropie...
The degree-based network entropy which is inspired by Shannon’s entropy concept becomes the informat...
Many graph invariants have been used for the construction of entropy-based measures to characterize ...
The degree-based entropy Id(G) of a graph G on m>0 edges is obtained from the well-known Shannon ent...
In this article, we discuss the problem of establishing relations between information measures for n...
In this article, we discuss the problem of establishing relations between information measures for n...
A variety of problems in, e.g., discrete mathematics, computer science, information theory, statisti...
The entropy-based procedures from the configuration of chemical graphs and multifaceted networks, se...
Abstract. Generalised degrees provide a natural bridge between local and global topological properti...
A graph’s entropy is a functional one, based on both the graph itself and the distribution of probab...
The first degree-based entropy of a graph is the Shannon entropy of its degree sequence normalized b...
The aim of this report to solve the open problem suggested by Chen et al. We study the graph entropy...
In this paper we derive entropy bounds for hierarchical networks. More precisely, starting from a re...
For measuring the complexity of a graph, an information-theoretic quantity, that is, entropy functio...
The graph entropies inspired by Shannon’s entropy concept become the information-theoretic quantitie...
Inspired by the generalized entropies for graphs, a class of generalized degree-based graph entropie...
The degree-based network entropy which is inspired by Shannon’s entropy concept becomes the informat...
Many graph invariants have been used for the construction of entropy-based measures to characterize ...
The degree-based entropy Id(G) of a graph G on m>0 edges is obtained from the well-known Shannon ent...
In this article, we discuss the problem of establishing relations between information measures for n...
In this article, we discuss the problem of establishing relations between information measures for n...
A variety of problems in, e.g., discrete mathematics, computer science, information theory, statisti...
The entropy-based procedures from the configuration of chemical graphs and multifaceted networks, se...
Abstract. Generalised degrees provide a natural bridge between local and global topological properti...
A graph’s entropy is a functional one, based on both the graph itself and the distribution of probab...
The first degree-based entropy of a graph is the Shannon entropy of its degree sequence normalized b...
The aim of this report to solve the open problem suggested by Chen et al. We study the graph entropy...
In this paper we derive entropy bounds for hierarchical networks. More precisely, starting from a re...
For measuring the complexity of a graph, an information-theoretic quantity, that is, entropy functio...