An annealed 'neural gas' network for robust vector quantization

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

Volumn 1112 LNCS, Issue , 1996, Pages 151-156

  Hofmann, Thomas ^a   Buhmann, Joachim M ^a  

^a UNIVERSITY OF BONN   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER PROGRAMMING; DATA COMPRESSION; INFERENCE ENGINES; NEURAL NETWORKS; VECTORS;

BANDWIDTH LIMITATION; CODEBOOK DESIGN; COMPETITIVE NEURAL NETWORK; DETERMINISTIC ANNEALING ALGORITHMS; ENTROPY INFERENCE; INFORMATION SOURCES; OBJECTIVE FUNCTIONS; OPTIMALITY CRITERIA; ONLINE PROBLEMS;

VECTOR QUANTIZATION;

EID: 84902208214     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-61510-5_29     Document Type: Conference Paper

References (12)

1. J. M. Buhmann and H. Kühnel. Complexity optimized data clustering by competitive neural networks. Neural Computation, 5:75-88, 1993.
2. J. M. Buhmann and H. Kühnel. Vector quantization with complexity costs. IEEE Transactions on Information Theory, 39(4): 1133-1145, July 1993.
3. A. Gersho and R. M. Gray. Vector Quantization and Signal Processing. Kluwer Academic Publisher, Boston, 1992.
4. T. Kohonen. Self-organization and Associative Memory. Springer, Berlin, 1984.
5. J.J. Kosowsky and A.L. Yuille. The invisible hand algorithm: solving the assignment problem with statistical mechanics. Neural Computation, 7(3):477-490, 1994.
6. Y. Linde, A. Buzo, and R. M. Gray. An algorithm for vector quantizer design. IEEE Transactions on Communications, 28:84-95, 1980.
7. S.P. Luttrell. Hierarchical vector quantizations. IEE Proceedings, 136:405-413, 1989.
8. J. MacQueen. Some methods for classification and analysis of multivariate observations. In Proceedings of the 5th Berkeley Symposium on Mathematical Statistics and Probability, pages 281-297, 1967.
9. S. Mallat. A theory for multidimensional signal decomposition: The wavelet representation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 11 (7):674-693, 1989.
10. T.M. Martinetz, S. G. Berkovich, and K. J. Schulten. 'neural-gas' network for vector quantization and its application to time-series prediction. IEEE Transactions on Neural Networks, 4(4):558-569, 1993.
11. K. Rose, E. Gurewitz, and G. Fox. Statistical mechanics and phase transitions in clustering. Physical Review Letters, 65(8):945-948, 1990.
12. R. Sinkhom. A relationship between arbitrary positive matrices and doubly stochastic matrices. Ann. Math. Statist., 35:876-879, 1964.