Granular enhancement of fuzzy-ART/SOM neural classifiers based on lattice theory

Studies in Computational Intelligence

Volumn 67, Issue , 2007, Pages 3-23

  Kaburlasos, Vassilis G ^a  

^a TECHNOLOGICAL EDUCATIONAL INSTITUTE OF KAVALA   (Greece)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 34347391248     PISSN: 1860949X     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-540-72687-6_1     Document Type: Article

References (37)

1. Andonie R, Sasu L (2006) Fuzzy ARTMAP with input relevances. IEEE Trans Neural Networks 17(4):929-941
2. Bargiela A, Pedrycz W, Hirota K (2004) Granular prototyping in fuzzy clustering. IEEE Trans Fuzzy Systems 12(5):697-709
3. Birkhoff G (1967) Lattice Theory. American Math Society, Colloquium Publications XXV
4. Bishop CM, Svensén M, Williams CKI (1998) GTM: The generative topographic mapping. Neural Computation 10(1):215-234
5. Carpenter GA, Grossberg S, Rosen DB (1991) Fuzzy ART: Fast stable learning and categorization of analog patterns by an adaptive resonance system. Neural Networks 4(6):759-771
6. Carpenter GA, Grossberg S, Markuzon N, Reynolds JH, Rosen DB (1992) Fuzzy ARTMAP: A neural network architecture for incremental supervised learning of analog multidimensional maps. IEEE Trans Neural Networks 3(5):698-713
7. Castro J, Georgiopoulos M, DeMara R, Gonzalez A (2005) Data-partitioning using the Hilbert space filling curves: Effect on the speed of convergence of Fuzzy ARTMAP for large database problems. Neural Networks 18(7):967-984
8. Castro J, Secretan J, Georgiopoulos M, DeMara RF, Anagnostopoulos G, Gonzalez AJ (2007) Pipelining of fuzzy-ARTMAP without match-tracking: Correctness, performance bound, and beowulf evaluation. Neural Networks 20(1):109-128
9. Cripps A, Nguyen N (2007) Fuzzy lattice reasoning (FLR) classification using similarity measures. This volume, Chapter 13
10. Georgiopoulos M, Fernlund H, Bebis G, Heileman GL (1996) Order of search in fuzzy ART and fuzzy ARTMAP: Effect of the choice parameter. Neural Networks 9(9):1541-1559
11. Goguen JA (1967) L-fuzzy sets. J Math Analysis and Applications 18:145-174
12. Graña M, Sussner P, Ritter G (2003) Innovative applications of associative morphological memories for image processing and pattern recognition. Mathware & Soft Computing 10(2-3):155-168
13. Hammer B, Villmann T (2002) Generalized relevance learning vector quantization. Neural Networks 15(8-9):1059-1068
14. Hatzimichailidis A, Kaburlasos VG, Papadopoulos B (2006) An implication in fuzzy sets. In: Proc World Congress Computational Intelligence (WCCI) FUZZIEEE Program pp 203-208
15. Igel C, Temme KH (2004) The chaining syllogism in fuzzy logic. IEEE Trans Fuzzy Systems 12(6):849-853
16. Kaburlasos VG (1992) Adaptive Resonance Theory with Supervised Learning and Large Database Applications. PhD Thesis, Univ Nevada, Reno
17. Kaburlasos VG (2004) FINs: Lattice theoretic tools for improving prediction of sugar production from populations of measurements. IEEE Trans Systems, Man and Cybernetics - B, Cybernetics 34(2):1017-1030
18. Kaburlasos VG (2006) Towards a Unified Modeling and Knowledge-Representation Based on Lattice Theory - Computational Intelligence and Soft Computing Applications, ser Studies in Computational Intelligence 27. Springer, Heidelberg, Germany
19. Kaburlasos VG, Athanasiadis IN, Mitkas PA (2007) Fuzzy lattice reasoning (FLR) classifier and its application for ambient ozone estimation. Intl J Approximate Reasoning 45(1):152-188
20. Kaburlasos VG, Chatzis V, Tsiantos V, Theodorides M (2005) granular Self-Organizing Map (grSOM) neural network for industrial quality control. In: Astola JT, Tabus I, Barrera J (eds) Proc SPIE Math Methods in Pattern and Image Analysis 5916 pp 59160J:1-10
21. Kaburlasos VG, and Kehagias A (2007) Novel fuzzy inference system (FIS) analysis and design based on lattice theory. IEEE Trans Fuzzy Systems 15(2):243-260
22. Kaburlasos VG, Papadakis SE (2006) Granular self-organizing map (grSOM) for structure identification. Neural Networks 19(5):623-643
23. Kaburlasos VG, Petridis V (2000) Fuzzy lattice neurocomputing (FLN) models. Neural Networks 13(10):1145-1170
24. Karayiannis NB, Bezdek JC (1997) An integrated approach to fuzzy learning vector quantization and fuzzy c-means clustering. IEEE Trans Fuzzy Systems 5(4):622-628
25. Knuth KH (2007) Valuations on lattices: Fuzzification and its implications. This volume, Chapter 15
26. Kohonen T (1995) Self-Organizing Maps, ser Information Sciences 30. Springer.
27. Lin TY (2005) Introduction to special issues on data mining and granular computing (editorial). Intl J Approximate Reasoning 40(1-2):1-2
28. Liu J, Ruan D, Xu Y, Song Z (2003) A resolution-like strategy based on a lattice-valued logic. IEEE Trans Fuzzy Systems 11(4):560-567
29. Papadakis SE, Kaburlasos VG (submitted) Efficient structure identification in TSK models based on a novel self-organizing map (SOM)
30. Pedrycz W (2005) Knowledge-Based Clustering - From Data to Information Granules. John Wiley & Sons, Hoboken, NJ
31. Peltonen J, Klami A, Kaski S (2004) Improved learning of Riemannian metrics for exploratory analysis. Neural Networks 17(8-9):1087-1100
32. Piedra-Fernández JA, Cantón-Garbín M, Guindos-Rojas F (2007) Application of fuzzy lattice neurocomputing (FLN) in ocean satellite images for pattern recognition. This volume, Chapter 11
33. Popescu M, Gader P, Keller JM (2006) Fuzzy spatial pattern processing using linguistic hidden Markov models. IEEE Trans Fuzzy Systems 14(1):81-92
34. Ritter GX, Gader PD (2006) Fixed points of lattice transforms and lattice associative memories. In: Hawkes P (ed) Advances in Imaging and Electron Physics 144:165-242. Elsevier, Amsterdam, The Netherlands
35. Ritter GX, Urcid G (2003) Lattice algebra approach to single-neuron computation. IEEE Trans Neural Networks 14(2):282-295
36. Sussner P, Valle ME (2006) Gray-scale morphological associative memories. IEEE Trans Neural Networks 17(3):559-570
37. Vuorimaa P (1994) Fuzzy self-organizing map. Fuzzy Sets Syst 66(2):223-231