Abstract: The system and method for determining the feedback capacity of information distributed in a complex network determines feedback capacity as information is received and diffused throughout the network. Traditionally, real networks, such as computer networks, were used in determining network feedback. However, current complex networks typically incorporate graphing models for network analysis. The system and method provide a process to determine the quality of a complex network with respect to feedback capacity, such as can be determined by a corresponding Belief Propagation algorithm and a corresponding entropy equation. The system and method can also determine the cyclic entropy per penetration in a complex network, the depth penetration for nodes in the complex network and a plurality of cycle counts per node in the complex network based on a source node.

Abstract: The system and method for determining the feedback capacity of information distributed in a complex network determines feedback capacity as information is received and diffused throughout the network. Traditionally, real networks, such as computer networks, were used in determining network feedback. However, current complex networks typically incorporate graphing models for network analysis. The system and method provide a process to determine the quality of a complex network with respect to feedback capacity, such as can be determined by a corresponding Belief Propagation algorithm and a corresponding entropy equation. The system and method can also determine the cyclic entropy per penetration in a to complex network, the depth penetration for nodes in the complex network and a plurality of cycle counts per node in the complex network based on a source node.