Modeling Networks with Dynamic Topologies

Resonant Converters : Topologies , Dynamic Modeling and Control

Recent interest in high frequency resonant converters has prompted this exploration of aspects that have not previously been studied carefully. More specifically, this thesis examines possible methods for deriving resonant converter topologies and show how to develop dynamic models for converter behavior, demonstrates the design and implementation of control schemes based on these models. Syste...

Beyond Knowledge Tracing: Modeling Skill Topologies with Bayesian Networks

Modeling and predicting student knowledge is a fundamental task of an intelligent tutoring system. A popular approach for student modeling is Bayesian Knowledge Tracing (BKT). BKT models, however, lack the ability to describe the hierarchy and relationships between the different skills of a learning domain. In this work, we therefore aim at increasing the representational power of the student m...

Computational modeling of dynamic decision making using connectionist networks

In this research connectionist modeling of decision making has been presented. Important areas for decision making in the brain are thalamus, prefrontal cortex and Amygdala. Connectionist modeling with 3 parts representative for these 3 areas is made based the result of Iowa Gambling Task. In many researches Iowa Gambling Task is used to study emotional decision making. In these kind of decisio...

Modeling and Control of Gas Turbine Combustor with Dynamic and Adaptive Neural Networks (TECHNICAL NOTE)

Modeling Epidemics with Dynamic Small-World Networks

In this presentation a minimal model for describing the spreading of an infectious disease, such as influenza, is discussed. Here it is assumed that spreading takes place on a dynamic small-world network comprising shortand long-range infection events. Approximate equations for the epidemic threshold as well as the spreading dynamics are derived and they agree well with numerical discrete time-...