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.