Savitha Ramasamy

Books

  1. Monograph: N. Sundararajan, S. Suresh, and R. Savitha, Supervised Learning Algorithms in the Complex Domain, Springer-Verlag, Springer Berlin Heidelberg, vol. 421, pp. 1-189, ISBN: 978-3-642-29490-7, 2013.
  2. Book Chapter: R. Savitha, S. Suresh and N. Sundararajan, A Projection based Sequential Learning Algorithm for a Fully complex-valued Relaxation Network, Recent Trends in Complex-Valued Neural Networks, IEEE Press CI Book Series, 2011. (Accepted)

International Journal Publications

  1. M. Sivachitra, R. Savitha, S. Suresh and S Vijayachitra, "A Fully Complex-valued Fast Learning Classifier (FC-FLC) for real-valued classification problems," Neurocomputing, vol. 149, pp. 198-206, 2015. [I.F.: 1.580].
  2. K. Subramanian, A. K. Das, S. Sundaram, and S. Ramasamy, "A meta-cognitive interval type-2 fuzzy inference system and its projection based learning algorithm," Evolving Systems, vol. 5, no. 4, pp. 219-230, 2014.
  3. K. Subramanian, R. Savitha, and S. Suresh, "A complex-valued neuro-fuzzy inference system and its learning mechanism," Neurocomputing, vol. 123, pp. 110-120, 2014. [I.F.: 1.580].
  4. K. Subramanian, R. Savitha, and S. Suresh, "A Metacognitive Complex-Valued Interval Type-2 Fuzzy Inference System," IEEE Transactions on Neural Networks and Learning Systems, vol. 25, no. 9, pp. 1659 - 1672, 2014. [I.F.: 2.952]
  5. R. Savitha, S. Suresh and H. J. Kim, “A Meta-cognitive Learning Algorithm for an Extreme Learning Machine Classifier,” Cognitive Computation, vol. 6, no. 2, pp. 253-263, 2014. [I.F.: 1.100]
  6. R. V. Babu, R. Savitha, S. Suresh, and B. Agarwal, "Subject independent human action recognition using spatio-depth information and meta-cognitive RBF network," Engineering Applications of Artificial Intelligence, vol. 26, no. 9, pp. 2010-2021, 2013.[I.F.: 1.962]
  7. R. Savitha, S. Suresh, and N. Sundararajan , “A Projection Based Fast Learning Fully Complex-valued Relaxation Neural Network,” IEEE Transactions on Neural Networks, vol. 24, no. 4, pp. 529-541, 2013. [I.F.: 2.952]
  8. R. Savitha, S. Suresh and N. Sundararajan, “Fast Learning Complex-valued Classifiers for Real-valued Classification Problems,” International Journal of Machine Learning and Cybernetics, vol. 4, no. 5, pp. 469-476, 2013.
  9. R. Venkatesh Babu, S. Suresh, and R. Savitha, “Human Action Recognition using a Fast Learning Fully Complex-valued Classifier,” Neurocomputing, vol. 89, pp. 202-212, 2012. [I.F.: 1.580].
  10. R. Savitha, S. Suresh and N. Sundararajan, "A Metacognitive Fully Complex-valued Relaxation Network,” Neural Networks, 2012. (Accepted) [I.F.: 1.955
  11. M. F. Amin, R. Savitha, M. I. Amin, and K. Murase, “Orthogonal Least Square based Complex-valued Functional Link Network,” Neural Networks, 2012. (Accepted) [I.F.: 1.955]
  12. R. Savitha, S. Suresh, and N. Sundararajan, "Meta-cognitive Learning in a Fully Complex-valued Radial Basis Function Neural Network,"Neural Computation, vol. 24, no. 5, pp. 1297-1328, 2012.[I.F.: 2.290]
  13. 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. [I.F. : 2.833]
  14. 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. [I.F.: 1.442]
  15.  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. 1061-1072, 2011. [I.F.: 2.633]
  16. R. Savitha, S. Suresh and N. Sundararajan, “A Fully Complex-valued Radial Basis Function Network and its Learning Algorithm,” International Journal of Neural systems, vol. 19, no. 4, pp 253 – 267, 2009. [I.F.: 4.237]
  17. R. Savitha, S. Suresh, N. Sundararajan, and P. Saratchandran, “A new  learning  algorithm with logarithmic performance index  for complex-valued neural  networks,”  Neurocomputing, vol. 72, no. 16-18, pp. 3771-3781, 2009. [I.F.: 1.442]

International Conference Publications


  1. M. Elangeeran, S. Ramasamy and K. Arumugam, "A novel method for benign and malignant characterization of mammographic microcalcifications employing waveatom features and circular complex valued Extreme Learning Machine," 2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP), 2014.
  2. B. S. Mahanand, R. Savitha and S Suresh, "Computer Aided Diagnosis of ADHD Using Brain Magnetic Resonance Images," AI 2013: Advances in Artificial Intelligence, pp. 386-395, 2013.
  3. S. Vigneshwaran, B. S. Mahanand, S. Suresh and R. Savitha "Autism spectrum disorder detection using projection based learning meta-cognitive RBF network," The 2013 International Joint Conference on Neural Networks (IJCNN), pp. 1-8, 2013.
  4. D. Shirin, R. Savitha and S. Suresh "A basis coupled evolving spiking neural network with afferent input neurons," The 2013 International Joint Conference on Neural Networks (IJCNN), pp. 1-8, 2013.
  5. B. Shamima, R. Savitha, S. Suresh, and S. Saraswathi, "Protein secondary structure prediction using a fully complex-valued relaxation network," The 2013 International Joint Conference on Neural Networks (IJCNN), pp. 1-8, 2013.
  6. K. Subramanian, R. Savitha, and S Suresh, "Zero-Error Density Maximization based learning algorithm for a neuro-fuzzy inference system," IEEE International Conference on Fuzzy Systems, pp. 1-7, 2013.
  7. K. Subramanian, R. Savitha and S. Suresh, “A Meta-Cognitive Interval Type-2 Fuzzy Inference System Classifier and its Projection Based Learning Algorithm,” 2013 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS), pp. 48-55, 2013.
  8. S. Kartick, R. Savitha, S. Suresh, “Complex neuro fuzzy inference system for wind prediction”, International Joint Conference on Neural Networks (IJCNN 2012), art. no. 6252812, 2012.
  9. G. S. Babu, R. Savitha and S. Suresh, “A Projection Based Learning in Meta-cognitive Radial Basis Function Network for Classification Problems,” International Joint Conference on Neural Networks (IJCNN 2012), art. no. 6252769, 2012.
  10. K. Subramanian, R. Savitha, S. Suresh, B. S. Mahanand, "Complex-valued neuro-fuzzy inference system based classifier," Swarm, Evolutionary, and Memetic Computing, pp. 348-355, 2012.
  11. M. F. Amin, R. Savitha, M. I.  Amin and K. Murase, “Complex-Valued Functional Link Network Design by Orthogonal Least Squares Method for Function Approximation Problems,” International Joint Conference on Neural Networks (IJCNN 2011), art. no. 6033400 , pp. 1489-1496, 2011.
  12. R. Savitha, S. Suresh and N. Sundararajan, “Nonlinear Complex-valued Extreme Learning Machine Classifier,”  International Joint Conference on Neural Networks (IJCNN 2011), art. no. 6033508 , pp. 2243-2249, 2011.
  13. S. Suresh, R. Savitha, and N. Sundararajan, “A fast learning Fully Complex-valued Relaxation Network (FCRN),” International Joint Conference on Neural Networks (IJCNN 2011), art. no. 6033384 , pp. 1372-1377, 2011.
  14. R. Savitha, S. Suresh, N. Sundararajan, and H. J. Kim, “Fast learning fully complex-valued classifiers for real-valued classification problems," D. Liu et al. (Eds.): ISNN 2011, Part I, Lecture Notes in Computer Science (LNCS), vol. 6675, pp. 602-609, 2011.
  15. G. Vani, R. Savitha and N. Sundararajan, “Classification of Abnormalities in Digitized Mammograms using Extreme Learning Machine,”, ICARCV 2010, Singapore.
  16. R. Savitha, S. Suresh and N. Sundararajan, “Regulatory System for Efficient Learning in Fully Complex-valued Radial Basis Function Network,”, presented in Proc. Of International Joint Conference on Neural Networks (IJCNN 2010), Barcelona (Spain), 2009.
  17. R. Savitha, S. Vigneshwaran, S. Suresh and N. Sundararajan, “Adaptive Beamforming using Complex-valued Radial Basis Function Neural Networks,” in IEEE Region 10 Conference (TENCON ’09), Singapore, pp. 1-6, Nov 23-26, 2009.
  18. R. Savitha, S. Suresh, and N. Sundararajan, "Complex-valued function approximation using a Fully complex-valued RBF (FC-RBF) learning algorithm," Proc. of International Joint Conference on Neural Networks 2009 (IJCNN 2009), Atlanta (Georgia, USA), pp. 2819–2825, 2009.
  19. K. Baskaran and R. Savitha, “Neural Network Controlled Gripper for Wire-Bonding Machines in Semiconductor Fabrication,” in International Conference on Mechatronics and  Machine Vision in Practice (M2VIP08), Auckland (New Zealand), pp. 323-326, 2008.
  20. R. Savitha, S. Suresh, N. Sundararajan and P. Saratchandran, Complex Function Approximation using an Improved BP Learning Algorithm for Feedforward Networks, In Proc. Of International Joint Conference on Neural Networks 2008 (IJCNN 2008), Hong Kong, pp. 2251–2258, 2008