References

1

W. H. Press, S. A. Teukolsky, W. T. Vetterling, and B. P. Flannery, Numerical Recipes in C: The art of scientific computing, Cambridge University Press, Cambridge, 1992.
(second edition).

2

J.-S. R. Jang and C.-T. Sun, ``Functional equivalence between radial basis function networks and fuzzy inference systems,'' IEEE Trans. on Neural Networks 4(1), pp. 156-159, 1993.

3

J. E. Moody and C. Darken, ``Fast learning in networks of locally-tuned processing units,'' Neural Computation 1, pp. 281-294, 1989.

4

Y. Linde, A. Buzo, and R. M. Gray, ``An algorithm for vector quantizer design,'' IEEE Transactions on Communication COM-28, pp. 84-95, 1980.

5

J. MacQueen, ``On convergence of k-means and partitions with minimum average variance,'' Ann. Math. Statist. 36, p. 1084, 1965.
abstract.

6

G. O. Stone, ``An analysis of the delta rule and the learning of statistical associations,'' in Parallel Distributed Processing, R. D. E. and J. L. McClelland, eds., vol. 1, pp. 444-459, MIT Press, Cambridge, 1986.

7

C. Bishop, Neural Networks for Pattern Recognition, Oxford University Press, 1995.

8

B. Fritzke, ``A growing neural gas network learns topologies ,'' in Advances in Neural Information Processing Systems 7, G. Tesauro, D. S. Touretzky, and T. K. Leen, eds., pp. 625-632, MIT Press, Cambridge MA, 1995.

9

T. M. Martinetz, ``Competitive Hebbian learning rule forms perfectly topology preserving maps,'' in ICANN'93: International Conference on Artificial Neural Networks, pp. 427-434, Springer, (Amsterdam), 1993.

10

S. M. Omohundro, ``The Delaunay triangulation and function learning ,'' tr-90-001, International Computer Science Institute, Berkeley, 1990.

11

B. Fritzke, ``Fast learning with incremental RBF networks ,'' Neural Processing Letters 1(1), pp. 2-5, 1994.

12

B. Fritzke, ``Supervised Learning with Growing Cell Structures ,'' in Advances in Neural Information Processing Systems 6, J. Cowan, G. Tesauro, and J. Alspector, eds., pp. 255-262, Morgan Kaufmann Publishers, San Mateo, CA, 1994.

13

B. Fritzke, ``Transforming hard problems into linearly separable ones with incremental radial basis function networks ,'' in HELNET International Workshop on Neural Networks, M. van der Heyden, J. Mrsic-Flögel, and K. Weigel, eds., pp. 54-63, VU University Press, (Amsterdam), 1996.