Complex-valued Self-regulatory Resource Allocation Network (CSRAN)

  • Sundaram Suresh
  • Narasimhan Sundararajan
  • Ramasamy Savitha
Part of the Studies in Computational Intelligence book series (SCI, volume 421)


All the algorithms described in the chapters 2, 3, 4 and 6, viz., FC-MLP, IC-MLP, CRBF, FC-RBF, Mc-FCRBF, FCRN and CC-ELM are batch learning algorithms. These algorithms require the complete training data set and the network structure has to be fixed a priori.


Extreme Learning Machine Hide Neuron Radial Basis Function Neural Network Network Parameter Training Sequence 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Deng, J.P., Sundararajan, N., Saratchandran, P.: Communication channel equalization using complex-valued minimal radial basis function neural networks. IEEE Transactions on Neural Networks 13(3), 687–696 (2002)CrossRefGoogle Scholar
  2. 2.
    Li, M.B., Huang, G.B., Saratchandran, P., Sundararajan, N.: Complex-valued growing and pruning RBF neural networks for communication channel equalisation. IEE Proceedings- Vision, Image and Signal Processing 153(4), 411–418 (2006)CrossRefGoogle Scholar
  3. 3.
    Yingwei, L., Sundararajan, N., Saratchandran, P.: A sequential learning scheme for function approximation using minimal radial basis function neural networks. Neural Computation 9(2), 461–478 (1997)CrossRefzbMATHGoogle Scholar
  4. 4.
    Huang, G.B., Saratchandran, P., Sundararajan, N.: An efficient sequential learning algorithm for growing and pruning RBF (GAP-RBF) networks. IEEE Transactions on Systems, Man, and Cybernetics - Part B: Cybernetics 34(6), 2284–2292 (2004)CrossRefGoogle Scholar
  5. 5.
    Savitha, R., Suresh, S., Sundararajan, N., Saratchandran, P.: A new learning algorithm with logarithmic performance index for complex-valued neural networks. Neurocomputing 72(16-18), 3771–3781 (2009)CrossRefGoogle Scholar
  6. 6.
    Goh, S.L., Mandic, D.P.: An augmented extended kalman filter algorithm for complex-valued recurrent neural networks. Neural Computation 19(4), 1039–1055 (2007)CrossRefzbMATHGoogle Scholar
  7. 7.
    Cha, I., Kassam, S.A.: Channel equalization using adaptive complex radial basis function networks. IEEE Journal on Selected Areas in Communications 13(1), 122–131 (1995)CrossRefGoogle Scholar
  8. 8.
    Suksmono, A.B., Hirose, A.: Intelligent beamforming by using a complex-valued neural network. Journal of Intelligent and Fuzzy Systems 15(3-4), 139–147 (2004)Google Scholar
  9. 9.
    Amin, M.F., Islam, M.M., Murase, K.: Ensemble of single-layered complex-valued neural networks for classification tasks. Neurocomputing 72(10-12), 2227–2234 (2009)CrossRefGoogle Scholar
  10. 10.
    Huang, G.B., Li, M.B., Chen, L., Siew, C.K.: Incremental extreme learning machine with fully complex hidden nodes. Neurocomputing 71(4-6), 576–583 (2008)CrossRefGoogle Scholar
  11. 11.
    Huang, G.B., Chen, L., Siew, C.K.: Universal approximation using incremental constructive feedforward networks with random hidden nodes. IEEE Transactions on Neural Networks 17(4), 879–892 (2006)CrossRefGoogle Scholar
  12. 12.
    Savitha, R., Suresh, S., Sundararajan, N.: A fully complex-valued radial basis function network and its learning algorithm. International Journal of Neural Systems 19(4), 253–267 (2009)CrossRefGoogle Scholar
  13. 13.
    Jianping, D., Sundararajan, N., Saratchandran, P.: Complex-valued minimal resource allocation network for nonlinear signal processing. International Journal of Neural Systems 10(2), 95–106 (2000)Google Scholar
  14. 14.
    Monzingo, R.A., Miller, T.W.: Introduction to Adaptive Arrays. SciTech. Publishing, Raleigh (2004)Google Scholar
  15. 15.
    Blake, C., Merz, C.: UCI repository of machine learning databases. Department of Information and Computer Sciences. University of California, Irvine (1998), Google Scholar

Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2013

Authors and Affiliations

  • Sundaram Suresh
    • 1
  • Narasimhan Sundararajan
    • 2
  • Ramasamy Savitha
    • 1
  1. 1.School of Computer EngineeringNanyang Technological UniversitySingaporeSingapore
  2. 2.School of Electrical and Electronics EngineeringNanyang Technological UniversitySingaporeSingapore

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