Curvilinear component analysis for high-dimensional data representation: I. theoretical aspects and practical use in the presence of noise

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 1607, Issue , 1999, Pages 625-634

  Hérault, Jeanny ^a   Jausions Picaud, Claire ^a   Guérin Dugué, Anne ^a  

^a GRENOBLE INSTITUTE OF TECHNOLOGY   (France)

Author keywords

[No Author keywords available]

Indexed keywords

NEURAL NETWORKS;

CURVILINEAR COMPONENT ANALYSIS; HIGH DIMENSIONAL DATA; INTRINSIC DIMENSIONS; NON LINEAR; NONLINEAR MAPPINGS; PRACTICAL USE; THEORETICAL ASPECTS; THEORETICAL FRAMEWORK;

CLUSTERING ALGORITHMS;

EID: 84958063257     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/BFb0100530     Document Type: Conference Paper

References (17)

1. Borg I. and Groenen P. (1997). Modern Multidimensional Scaling: Theory and Applications. Springer Series in Statistics.
2. Cirrincione G., Cirrincione M., Vitale G. (1994). " Diagnosis of Three-Phase converters Using the VQP Neural Network" 2nd IFAC Workshop on Computer Software Structures integrating AI/KBS System in Process Control, Lund, Sweden, 11/13 August 1994, 5 pages.
3. D’Aubigny G., L’analyse Multidimensionnelle des Données de Dissimilarités, These d’état, Université Grenoble I, 1989.
4. Demartines P. (1992). Mesures d’organisation du reseau de Kohonen. In M.Cottrell, editor, Congres Satellite du Congrès Europeen de Mathématiques: Aspects Théoriques des Reseaux de Neurones.
5. Demartines P. (1994). Analyse de données par réseaux de neurones auto-organisés. PhD thesis, Institut National Polytechnique de Grenoble.
6. Demartines P. and Herault J. (1997). Curvilinear Component Analysis: a Self-Organising Neural Network for Non-Linear Mapping of Data Sets, IEEE Trans, on Neural Networks, 8, 1, 148-154.
7. Gersho A. and Gray R. M. (1992). Vector quantization and signal compression. Kluwer Academic Publishers, London.
8. Guérin-Dugué A., Teissier P., Delso-Gafaro G. and Hérault J. (1999). Curvilinear Component Analysis for High-dimensional Data Representation: II. Examples of introducing additional mapping constraints for specific applications. Proceedings of IWANN’99, Alicante, Spain.
9. Herault J., Oliva A., Guerin-Dugue A. (1997). Scene Categorisation by Curvilinear Component Analysis of Low Frequency Spectra. European Symposium on Artificial Neural Networks, Bruges, BE.
10. Kohonen T. (1989). Self-Organisation and Associative Memory. Springer-Verlag, Berlin, 3rd edition.
11. Kruskal J.B. (1964). Non-metric multidimensional scaling: a numerical method. Psychometrika, 29:115-129.
12. Mardia K.V., Kent J.T., and Bibby J.M. (1979). Multivariate Analysis. Academic Press, London.
13. Sammon J.W. (1969). A non-linear mapping algorithm for data structure analysis. IEEE Trans. Computers, C-18(5):401-409.
14. Shepard R. N. (1962). The analysis of proximities: multidimensional scaling with an unknown distance function. Psychometrica, vol. 27, pp.125-139.
15. Siedlecki W., Siedlecka K., and Sklansky J. (1988). An overview of mapping techniques for exploratory pattern analysis. Pattern Recognition, 21(5):411-429.
16. Teissier P., Guérin-Dugué A., Schwartz J.L. (1998). Models for Audiovisual Fusion in a Noisy-Vowel Recognition Task, Journal of VLSI Signal Processing, vol 20, pp.25-44.
17. Vigneron V., Maiorov V., Berndt R. Sanz-Ortega J. J. and Schillebeeckx P. (1997). Neural network application to enrichment measurements with nai detectors. VCCSR Proceedings, Vienna, November 1997.