Large and distributed environments usually generate huge amounts of information. The easiest way to deal with this information in an uncoupled and asynchronous way is using event oriented approaches. These systems are usually implemented to react to the generated information. This paper presents a new track to add to these architectures a mechanism to discover behaviors combined with a reasonin...

In this research, an iterative approach is employed to recognize and classify control chart patterns. To do this, by taking new observations on the quality characteristic under consideration, the Maximum Likelihood Estimator of pattern parameters is first obtained and then the probability of each pattern is determined. Then using Bayes’ rule, probabilities are updated recursively. Finally, when...

Introduction: The adaptive rcsonance theory neural network (ART) as suggested by Grossberg [l] is a useful tool for pattern recognition. The original ART architecture (ART1 j, however, is capable of processing binary inputs only. The fuzzy ART [2] overcomes some of the limitations of ART1. While it has a similar architecture to that of ARTI, it can process continuous valued data, and has a fast...

abstractone of the methods for communications with various people's culture and art is to understand their views and beliefs as well as possible. in many cases, such beliefs appear in the forms of motifs and pictures drawn on artworks and historical-cultural artifacts; therefore, recognition of these patterns is of great importance in this regard. the meander pattern is one of such motifs ...

This work presents a technique for the analysis of Facial Electromyogram signal activities to classify five different facial expressions for Computer-Muscle Interfacing applications. Facial Electromyogram (FEMG) is a technique for recording the asynchronous activation of neuronal inside the face muscles with non-invasive electrodes. FEMG pattern recognition is a difficult task for the researche...