Fuzzy sets, uncertainty, and information
Fuzzy sets, uncertainty, and information
Fuzzy Sets and Systems - Special issue: fuzzy sets: where do we stand? Where do we go?
About the use of fuzzy clustering techniques for fuzzy model identification
Fuzzy Sets and Systems
Self-Organizing Maps
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Very Large Two-Level SOM for the Browsing of Newsgroups
ICANN 96 Proceedings of the 1996 International Conference on Artificial Neural Networks
Computing with Words in Information/Intelligent Systems 2: Applications
Computing with Words in Information/Intelligent Systems 2: Applications
Fuzzy logic = computing with words
IEEE Transactions on Fuzzy Systems
A fuzzy clustering-based rapid prototyping for fuzzy rule-based modeling
IEEE Transactions on Fuzzy Systems
Rule-based modeling of nonlinear relationships
IEEE Transactions on Fuzzy Systems
Supervised fuzzy clustering for rule extraction
IEEE Transactions on Fuzzy Systems
A fuzzy-logic-based approach to qualitative modeling
IEEE Transactions on Fuzzy Systems
Evolving a Bayesian classifier for ECG-based age classification in medical applications
Applied Soft Computing
Identification of ischemic heart disease via machine learning analysis on magnetocardiograms
Computers in Biology and Medicine
Mining, knowledge and decision support
Technology and Health Care
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In this study, we introduce and discuss a development of a highly interactive and user-friendly environment for an ECG signal analysis. The underlying neural architecture being a crux of this environment comes in the form of a self-organizing map. This map helps discover a structure in a set of ECG patterns and visualize a topology of the data. The role of the designer is to choose from some already visualized regions of the self-organizing map characterized by a significant level of data homogeneity and substantial difference from other regions. In the sequel, the regions are described by means of information granules-fuzzy sets that are essential in the characterization of the main relationships existing in the ECG data. The study introduces an original method of constructing membership functions that incorporates class membership as an important factor affecting changes in membership grades. The study includes a comprehensive descriptive modeling of highly dimensional ECG data.