Similarity Analysis and Knowledge Acquisition by Use of Evolving Neural Models and Fuzzy Decision

This chapter contains sections titled: Introduction Basics of Information Granulation The Fixed Unsupervised Learning Algorithm for Information Granulation Growing Learning Algorithms for Information Granulation Comparison of the Growing and the Fixed Learning Algorithms for Information Granulation Selection of Features for the Similarity Analysis Example of Similarity Analysis of Images Two-Parameter Fuzzy Rule-Based Similarity Analysis Unsupervised Classification for Knowledge Acquisition Conclusion References