This method is an extension of our previously described closed contour segmentation framework based on graph theory and dynamic programming (GTDP).
Algorithms of the first category are based on matrix theory concepts, while algorithms of the second one are based on graph theory concepts.
Manual segmentation was compared to an automated method based on graph theory, dynamic programming, and wavelet-based texture analysis.
Therefore, we designed a parallelization strategy based on graph theory.
Based on graph theory, this mechanism provides a way to adjust the distributed blackboard architecture.
Based on graph theory and Lyapunov stability theory, distributed coordinated attitude control laws are designed.
Then based on graph theory, nonsingular transformations are applied to the closed-loop multi-agent systems.
We propose a model to build a learning design recommendation system based on graph theory.
Based on graph theory, Lyapunov theory and Barbalat's Lemma, the stability of the controllers is proved.
To solve such problem, this paper presents a model for constructing agent blackboard communication architecture based on graph theory.
Referring to frames, characterized by large interaction between the beams, an analysis based on graph theory is proposed.
