REFERENCES
[1] Haykin, S.
(1999). Neural Networks: A
Comprehensive Foundation (2nd edition). pp368. Prentice
Hall.
[2] Jacobs, R.A., Jordan, M.I., & Barto, A.G. (1991).
Task Decomposition Through Competition in a Modular Connectionist
Architecture: The What and Where Vision Tasks.
Cognitive Science, 15, 219-250.
[3] Jacobs, R., Jordan, M., Nowlan, S., & Hinton, G. (1991).
Adaptive Mixtures of Local Experts.
Neural Computation, 3, 79-87.
[4] Jacobs, R., Jordan, M.
(1993). Hierarchical Mixture of
Experts $ the EM Algorithm. Neural Computation, 6 (2), 181-214.
[5] Liu, Y.,& Yao, X.
(?). Evolving Neural Networks
Which Generalise Well. Computational Intelligence Group, School of Computer
Science, University College, The University of New South Wales. Australian Defence Force Acadamy, Canberra,
ACT, Australia 2600.
[6] MacLeod, C.,& Maxwell, G.
(1999). Growing Artificial
Neural Networks using Evolutionary Algorithms.
School of Electronic &
Electrical Engineering, The Robert Gordon Luniversity, Aberdeen, Scotland.
[7] Mitchell, T.M. (1997). Machine
Learning. pp250. McGraw-Hill.
[8] Pratt, I. (1994). Artificial
Intelligence. pp224. The
Macmillan Press.
[9] Ramamurti, V.,& Ghosh, J. (?). On the Use of
Localized Gating in Mixture of Experts Networks. SBC Technology Resources,
Inc., 9505 Arboretum Blvd., Austin TX 78759, USA. Department of Electrical and Computer Engineering, UT Austin,
Austin TX 78712, USA.
[10] Ramamurti, V.,& Ghosh, J.
(?). Structurally Adaptive
Localized Mixtures of Experts for Non-Stationary Environments. Department
of Electrical and Computer Engineering. UT Austin. TX 78712-1084, USA.
[11] Yao, X.,& Darwen, P.
(1996). Speciation as Automatic Categorial Modulariztion. IEEE
Transactions on Evolutionary Compuation.