Senior Research Fellow of School of Electrical & Electronic Engineering

Books :


S. Suresh, N. Sundararajan and R. Savitha, Supervised Learning Algorithms with Complex-valued Neural Networks, Studies in Computational Intelligence 421, Springer-Verlag, 2013.

Journal  Papers:

R. Savitha, S. Suresh and  N. Sundararajan, “Projection-Based Fast Learning Fully Complex-Valued Relaxation Neural Network ,” IEEE  Transactions on Neural Networks, Vol.24, No.4,  pp. 529- 54 ,  April 2013.

K. Subramanian , S. Suresh and N. Sundararajan, “A Meta-Cognitive Neuro-Fuzzy Inference System (McFIS) for Sequential Classification Problems”,  IEEE Transactions on Fuzzy Systems,  2013.


R. Savitha, S. Suresh, N. Sundararajan, and H. J. Kim, “A Fully Complex-valued Radial Basis  Function Classifier for Real-valued Classification,” Neurocomputing, vol. 78, no. 1, 2012.


R. Savitha, S. Suresh and N. Sundararajan, “Fast Learning Circular Complex-valued Extreme Learning Machine (CC-ELM) for Real-valued Classification Problems,” Information Sciences, vol. 187, no. 1, pp. 277-290, 2012.


R. Savitha, S. Suresh and N. Sundararajan, “Metacognitive Learning in a Fully Complex-Valued Radial Basis Function Neural Network,”, Neural Computation, vol. 24, no. 5, pp. 1297-1328, 2012.


R. Savitha, S. Suresh, and N. Sundararajan, “A Metacognitive Fully Complex-valued Relaxation Network,” Neural Networks, 32, 209-218, 2012.


B.S. Mahanand, S. Suresh, N. Sundararajan and Aswatha Kumar, “Identification of brain regions responsible for Alzheimer’s disease using a Self-adaptive Resource Allocation Network ,” Neural Networks, 32, August, 2012, pp.313-322. 


S. Suresh, R. Savitha, and N. Sundararajan, “A Sequential Learning Algorithm for Complex- valued Self-regulatory Resource Allocation Network – CSRAN”, IEEE  Transactions on Neural Networks, Vol.22, No.7,  pp.1061-107 ,  July 2011.


Saras Saraswathi, Suresh Sundaram, Narasimhan Sundararajan, Michael Zimmermann, Marit Nilsen-Hamilton, "ICGA-PSO-ELM approach for Accurate Multiclass Cancer Classification Resulting in Reduced Gene Sets in which Genes Encoding Secreted Proteins are Highly Represented,  IEEE/ACM Transactions on Computational Biology and Bioinformatics, Vol.8,  No.2,  pp. 452 -463,  March-April, 2011


Rong, H.-J., Sundararajan, N., Huang, G.-B., Zhao, G.-S. “Extended sequential adaptive fuzzy inference system for classification problems”, (2011) Evolving Systems, 2 (2), pp. 71-82.