Abstract
An innovative neural fuzzy system is considered for cognitive design using a neural tree structure with nodes of neuronal type, where Gaussian function plays the role of membership function. The total tree structure effectively works as a fuzzy logic system. The structure of the tree is determined by domain knowledge and each node represents an entity of the domain of concern. The states of these entities are dependent on the stimuli at the input and the relationships between the stimuli and the states form the core for cognitive design. Namely, for each stimulus the status of the system is known and interpreted not only at the output but also at the granulated level concerning the system sub-domains. The research is described in detail and demonstrative applications are reported.
