Automatic analysis of signals with symbolic content

Artificial Intelligence in Medicine

Volumn 18, Issue 3, 2000, Pages 245-265

  Moreno, L ^a   Estevez J I ^a   Aguilar, R M ^a   Sanchez J L ^a   Sigut, J ^a   Pineiro J D ^a   Marichal, R ^a  

^a UNIVERSIDAD DE LA LAGUNA   (Spain)

Author keywords

EEG automatic analysis; Fuzzy system design; Signal to symbol translation; Trend detection

Indexed keywords

ELECTROENCEPHALOGRAPHY; FUZZY SETS; KNOWLEDGE BASED SYSTEMS; LEARNING SYSTEMS; MEMBERSHIP FUNCTIONS;

SIGNAL TO SYMBOL TRANSLATION;

MEDICAL COMPUTING;

ARTICLE; AUTOMATION; ELECTROENCEPHALOGRAPHY; METHODOLOGY; MODEL; PRIORITY JOURNAL;

ARTIFICIAL INTELLIGENCE; AUTOMATIC DATA PROCESSING; ELECTROENCEPHALOGRAPHY; FUZZY LOGIC; HUMANS; MATHEMATICAL COMPUTING; SLEEP; SYMBOLISM;

EID: 0034160007     PISSN: 09333657     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0933-3657(99)00043-3     Document Type: Article

References (22)

1. Bellazzi R., Ironi L., Guglielmann R., Stefanelli M. Qualitative models and fuzzy systems: an integrated approach for learning from data. Art. Intell. Med. 14(1-2):1998;5.
2. Carpenter GA, Grossberg S. Learning categorization, rule formation, and prediction by fuzzy neural networks, Fuzzy Logic and Neural Network Handbook. McGraw-Hill, 1996.
3. Carpenter GA, Grossberg S. The aRT of adaptive pattern recofnition by a self-organizing neural network, IEEE Computer 1988; 77-88.
4. Chatfield C, Collins A. Introduction to Multivariate Analysis. Chapman and Hall, 1980.
5. Jang JSR, Sun CT, Mizutani E. Neuro-Fuzzy and Soft Computing. Prentice-Hall, 1997.
6. Jobert M., Schulz H., Jahning P., Tismer C., Bes F., Escola H. A Computerized method for detecting episodes of wakefulness during sleep based on the alpha slow-wave index (ASI). Sleep. 17(1):1994;37-46.
7. Kosko B. Neural Networks and Fuzzy Systems. Prentice Hall, 1992.
8. Kuntsevich A, Kappel F. The Solver for Local Nonlinear Optimization Problems (version 1.1, Matlab, C, FORTRAN). University of Graz, Graz, 1997.
9. Leow W.K., Miikkulainen R. VISOR: Schema-based scene analysis with structured neural networks. Neural Proc. Lett. 1(2):1994;18-23.
10. Moreno L., Estévez J., Sánchez J., Mañas S., Merino J., Sigut J. et al. The management of symbolic strings using signal processing techniques and its application on the analysis of biomedical data. SCI Proceedings. 3:1997;446-453.
11. Moreno L., Estévez J., Sánchez J., Mañas S., Merino J., Sigut J. et al. The haar orthonormal filter bank under a fuzzyfied algebra and its application to the processing of epileptiform spikes. ICSPAT Conference Proceedings. 1:1997;368-372.
12. Nauck D, Kruse R. Obtaining interpretable fuzzy classification rules from medical data, Art. Intell. Med., 16(2):149-169.
13. Sloman A. On designing a visual system: towards a Gibsonian computational model of vision. J. Exp. Theoretical AI. 1(4):1989;289-337.
14. Steimann F., Adlassning K. Clinical monitoring with fuzzy automata. Fuzzy Sets Sys. 61:1994;37-42.
15. Steimann F. The interpretation of time-varying data with DIAMON-1. Art. Intell. Med. 8:1996;343-357.
16. Trauwaert E., Kaufman L., Rousseeuw P. Fuzzy clustering algorithms based on the maximum likelihood principle. Fuzzy Sets Syst. 42:1991;213-227.
17. Turksen I.B. Measurement of membership functions and their acquisition. Fuzzy Sets Syst. 40:1991;5-38.
18. Vaidyanathan PP. Multirate Systems And Filter Banks. Prentice Hall, 1993.
19. Valente de Oliveira J. A design methodology for fuzzy system interfaces. IEEE Trans. Fuzzy Sys., 1995;3(4).
20. Virant J., Zimic N. Fuzzy Automata with Fuzzy Relief. IEEE Trans. Fuzzy Sys. 3(1):1995;69-73.
21. Yen J, Wang L. Simplifying fuzzy rule-based models using orthogonal transformation methods, IEEE Trans. Sys., Man, And Cybernetics 1999;29(1).
22. Zadeh L.A. Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets Syst. 1:1978;3-28.