1. Rajaguru, H. and S.K. Prabhakar, 2017. KNN Classifier and K-Means Clustering for Robust Classification of Epilepsy from EEG Signals-A Detailed Analysis. Anchor Academic Publishing, Hamburg, Germany, ISBN-13: 9783960671404, Pages: 56.
2. Rajaguru, H. and S.K. Prabhakar, 2017. Comprehensive Analysis of Swarm Based Classifiers and Bayesian Based Models for Epilepsy Risk Level Classification from EEG Signals. Anchor Academic Publishing, Hamburg, Germany, ISBN-13: 978-3960671220, Pages: 47.
3. Mullai, K.K. and R.H. Kumar, 2017. Intelligent control based dynamic power tracking for wind energy conversion system. Asian J. Res. Social Sci. Humanit., 7: 975-984.
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4. Jothi, M., N.B. Balamurugan and R.H. Kumar, 2017. Performance analysis of fuzzy processor for a healthcare application-diabetic epilepsy risk classifier. Asian J. Res. Social Sci. Humanities, 7: 124-140.
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5. Rajaguru, H., K. Ganesan and V.K. Bojan, 2016. Earlier detection of cancer regions from MR image features and SVM classifiers. Int. J. Imag. Syst. Technol., 26: 196-208.
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6. Rajaguru, H. and S.K. Prabhakar, 2016. Variational Bayesian matrix factorization and certain post classifiers for classification of epilepsy from EEG signals. Res. J. Pharm. Technol., 9: 750-754.
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7. Rajaguru, H. and S.K. Prabhakar, 2016. LDA, GA and SVM’s for classification of epilepsy from EEG signals. Res. J. Pharm. Biol. Chem. Sci., 7: 2044-2049.
8. Rajaguru, H. and S.K. Prabhakar, 2016. Comprehensive Analysis of Extreme Learning Machine and Continuous Genetic Algorithm for Robust Classification of Epilepsy from EEG Signals. Anchor Academic Publishing, Hamburg, Germany, ISBN-13: 9783960675990, Pages: 32.
9. Rajaguru, H. and S.K. Prabhakar, 2016. Clinical health care for long distance using matrix factorization and mahalanobis based sparse representation measures for epilepsy classification from EEG signals. Int. J. Pharm. Sci. Rev. Res., 38: 144-148.
10. Rajaguru, H. and S.K. Prabhakar, 2016. An exhaustive analysis of code converters as pre-classifiers and K means, SVD, PCA, EM, MEM, PSO, HPSO and MRE as post classifiers for classification of epilepsy from EEG signals. J. Chem. Pharm. Sci., 9: 818-822.
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11. Rajaguru, H. and S.K. Prabhakar, 2016. A versatile approach to epilepsy classification using approximate entropy as post classifier. Int. J. Curr. Pharm. Rev. Res., 7: 166-170.
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12. Rajaguru, H. and S.K. Prabhakar, 2016. A unique approach to epilepsy classification from EEG signals using dimensionality reduction and neural networks. Circuits Syst., 7: 1455-1464.
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13. Rajaguru, H. and S.K. Prabhakar, 2016. A framework for epilepsy classification using modified sparse representation classifiers and naive Bayesian classifier from electroencephalogram signals. J. Med. Imag. Health Inform., 6: 1829-1837.
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14. Prabu, R., R. Harikumar and S. Raghavan, 2016. Performance analysis of ELM classifier for classification of electrical impedance tomography (EIT) images with infinite feature selection. Asian J. Res. Social Sci. Humanities, 6: 381-389.
15. Prabu, R. and R. Harikumar, 2016. A performance analysis of GA-ELM classifier in classification of abnormality detection in electrical impednce tomography (EIT) lung images. J. Scient. Ind. Res., 75: 404-411.
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16. Prabu, R. and R. Harikumar, 2016. A performance analysis of GA-ELM classifier in classification of abnormality detection in electrical impednce tomography (EIT) lung images. Asian J. Res. Social Sci. Humanities, 6: 1935-1948.
17. Prabhakar, S.K. and H. Rajaguru, 2016. Utilizing genetic algorithms with dimensionality reduction techniques for epilepsy classification from EEG signals. Int. J. Pharm. Technol., 8: 11334-11346.
18. Prabhakar, S.K. and H. Rajaguru, 2016. Soft thresholding techniques with PCA as post classifier for epilepsy risk level classification. Int. J. Pharm. Bio Sci., 7: 687-693.
19. Prabhakar, S.K. and H. Rajaguru, 2016. ICA, LGE and FMI as dimensionality reduction techniques followed by GMM as post classifier for the classification of epilepsy risk levels from EEG signals. Int. J. Simul. Syst. Sci. Technol., 17: 27.1-27.8.
20. Prabhakar, S.K. and H. Rajaguru, 2016. Code converters with city block distance measures for classifying epilepsy from EEG signals. Proc. Comput. Sci., 87: 5-11.
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21. Prabhakar, S.K. and H. Rajaguru, 2016. Classification of epilepsy risk using variable thresholding based feature extraction technique and suitable post classifiers. Int. J. Simul. Syst. Sci. Technol., 17: 28.1-28.8.
22. Prabhakar, S.K. and H. Rajaguru, 2016. Analysis of epilepsy classification from EEG signals using dimensionality reduction techniques with ApEn and SRC as post classifiers. Int. J. Adv. Eng. Technol., 7: 486-489.
23. Mullai, K.K., R. Harikumar and P. Santhoshini, 2016. Fuzzy logic control based permanent magnet synchronous generator with sepic converter for wind energy conversion system. Middle-East J. Scient. Res., 24: 142-148.
24. Manjurathi, B. and R.H. Rajaguru, 2016. Analysis of test data compression and power reduction using multiple encoding for Opto electronic circuits. J. Optoelectronics Adv. Mater., 18: 112-117.
25. Manimekalai, P., R. Harikumar and S. Raghavan, 2016. SOGI algorithm-based shunt active power filter for grid integration of photovoltaic systems. J. Circuits Syst. Comput., Vol. 25. 10.1142/S0218126616500468.
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26. Kumar, B.V., R.H. Kumar, G. Karthick and P.S. Kumar, 2016. Medical image segmentation based on minimization of region-scalable fitting energy. Asian J. Res. Social Sci. Humanities, 6: 830-840.
27. Kowsalya, P.K. and R. Harikumar, 2016. Performance analysis of adaptive routing structure for wireless sensor network based on load balancing. Wireless Personal Commun., 90: 473-485.
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28. Harikumar, R., P.S. Kumar and M. Manjusha, 2016. Comparison of support vector machine with particle swarm optimization technique for epilepsy classification from EEG. Int. J. Pharm. Technol., 8: 11904-11915.
29. Harikumar, R., P.S. Kumar and M. Manjusha, 2016. Performance analysis of original particle swarm optimization and modified PSO technique for robust classification of epilepsy risk level from EEE signals. Int. J. Pharm. Technol., 8: 18273-18283.
30. Harikumar, R. and P.S. Kumar, 2016. Optimization of fuzzy output through gaussian mixture model for epilepsy detection. Res. J. Pharm. Biol. Chem. Sci., 7: 105-113.
31. Harikumar, R. and P.S. Kumar, 2016. Intelligent computing techniques for epilepsy classification from EEG signals utilized for wireless telemedicine systems. Int. J. Pharm. Technol., 8: 11874-11885.
32. Harikumar, R. and P.S. Kumar, 2016. Efficient automatic seizure detection algorithms to classify epilepsy from EEG signals using certain post classifiers. Int. J. Pharm. Sci. Rev. Res., 41: 337-343.
33. Harikumar, R. and P.S. Kumar, 2016. Assessment of epilepsy classification using techniques such as singular value decomposition, approximate entropy and weighted k-nearest neighbors measures. Asian J. Pharm. Clin. Res., 9: 91-96.
34. Harikumar, R. and P.S. Kumar, 2016. An approach towards wireless telemedicine application with reduced PAPR and BER for epilepsy classification. Int. J. Pharm. Sci. Rev. Res., 39: 330-337.
35. Harikumar, R. and B. Manjurathi, 2016. Test data compression and power reduction using similarity based reordering technique for wireless systems. Wireless Personal Commun., 90: 713-728.
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36. Rajaguru, H., S.K. Prabhakar and V.K. Bojan, 2015. Clinical Significance of PPG Signals-An Engineering Perspective. Lambert Academic Publishing, Germany, ISBN: 978-3-659-67854-7, Pages: 72.
37. Rajaguru, H. and S.K. Prabhakar, 2015. A comprehensive review on photoplethysmography and its application for heart rate turbulence clinical diagnosis. Adv. Sci. Lett., 21: 3602-3604.
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38. Priya, K., R. Harikumar and B.V. Kumar, 2015. A comparison of extreme learning machine and neural network in the classification of epilepsy risk levels from EEG signals. Int. J. Applied Eng. Res., 10: 7167-7173.
39. Prabu, R. and R. Harikumar, 2015. Electrical impedance tomography (EIT) image classification using GLCM based feature extraction in artificial neural network (ANN). Int. J. Applied Eng. Res., 10: 28828-28833.
40. Prabhakar, S.K., H. Rajaguru and V.K. Bojan, 2015. Feature Extraction and Different Classifiers Applied for Detection of Abnormalities in Computer Tomography (CT) Images. Grin Academic Publishing Co., Germany, ISBN-13: 9783656894544, Pages: 34.
41. Prabhakar, S.K. and H. Rajaguru, 2015. Analysis of centre tendency mode chaotic modeling for electroencephalography signals obtained from an epileptic patient. Adv. Stud. Theor. Phys., 9: 171-177.
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42. Nirmalakumari, K., R. Harikumar and P. Rajkumar, 2015. Clustering techniques from significance analysis of microarrays. Adv. Intell. Syst. Comput., 412: 181-194.
43. Manimekalai, P., R.H. Kumar and S. Raghavan, 2015. Enhancement of fuzzy controlled photovoltaic-diesel system with battery storage using interleaved converter with hybrid MPPT for rural home. J. Solar Energy Eng., Vol. 137. 10.1115/1.4031514.
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44. Manimekalai, P. and R. Harikumar, 2015. H-bridge inverter with sinusoidal pulse width modulation technique using Uni polar switching for PV applications. Int. J. Applied Eng. Res., 10: 11480-11484.
45. Kumar, P.S. and R. Harikumar, 2015. Performance analysis of ApEn as a feature extraction technique and time delay neural networks, multi layer perceptron as post classifiers for the classification of epilepsy risk levels from EEG signals. Adv. Intell. Syst. Comput., 412: 89-97.
46. Kowsalya, P.K., R. Harikumar and R. Valarmathi, 2015. Prolong the life time of WSN sink mobility of PEGASIS with BFO. Int. J. Applied Eng. Res., 10: 23417-23422.
47. Kowsalya, P.K. and R. Harikumar, 2015. Energy efficient adaptive broadcasting scheme for wireless sensor networks. ARPN J. Eng. Applied Sci., 10: 1970-1974.
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48. Harikumar, R., P.S. Kumar and B.V. Kumar, 2015. An Illustrated Survey on Basic Communication Laboratories. Anchor Academic Publishing, Hamburg, Germany, Pages: 72.
49. Harikumar, R. and T. Vijayakumar, 2015. Analysis of wavelet transforms and RBF neural networks for epilepsy risk level classification from EEG signals. Int. J. Applied Eng. Res., 10: 19783-19788.
50. Harikumar, R. and T. Vijayakumar, 2015. A real time experimental setup for classification of epilepsy risk levels. Applied Soft Comput., 35: 493-501.
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51. Harikumar, R. and P.S. Kumar, 2015. Statistical techniques for the analysis of electroencephalography signals from epileptic patients. J. Chem. Pharm. Res., 7: 841-845.
52. Harikumar, R. and P.S. Kumar, 2015. Principal component analysis as a dimensionality reduction technique and sparse representation classifier as a post classifier for the classification of epilepsy risk levels from EEG signals. J. Pharm. Sci. Res., 7: 282-284.
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53. Harikumar, R. and P.S. Kumar, 2015. Performance comparison of EM, MEM, CTM, PCA, ICA, entropy and MI for photoplethysmography signals. Biomed. Pharmacol. J., 8: 413-418.
54. Harikumar, R. and P.S. Kumar, 2015. Performance analysis using code converter approach and the application of approximate entropy as post classifier for the classification of epilepsy risk levels from EEG signals. Asian J. Pharm. Clin. Res., 8: 287-290.
55. Harikumar, R. and P.S. Kumar, 2015. Fuzzy techniques and aggregation operators in classification of epilepsy risk levels for diabetic patients using EEG signals and cerebral blood flow. J. Biomater. Tissue Eng., 5: 316-322.
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56. Harikumar, R. and P.S. Kumar, 2015. Fuzzy mutual information as a dimensionality reduction technique for epileptic electroencephalography signals. Res. J. Applied Sci. Eng. Technol., 10: 1035-1037.
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57. Harikumar, R. and P.S. Kumar, 2015. Frequency behaviours of electroencephalography signals in epileptic patients from a wavelet thresholding perspective. Applied Math. Sci., 9: 2451-2457.
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58. Harikumar, R. and P.S. Kumar, 2015. Dimensionality reduction with linear graph embedding technique for electroencephalography signals of an epileptic patient. Res. J. Pharm. Technol., 8: 554-556.
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59. Harikumar, R. and P.S. Kumar, 2015. Dimensionality reduction techniques for processing epileptic encephalographic signals. Biomed. Pharmacol. J., 8: 103-106.
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60. Harikumar, R. and P.S. Kumar, 2015. Classifiers for the epilepsy risk level classification from electroencephalographic signals. Res. J. Pharm. Biol. Chem. Sci., 6: 469-474.
61. Harikumar, R. and P.S. Kumar, 2015. Analysis of singular value decomposition as a dimensionality reduction technique and sparse representation classifier as a post classifier for the classification of epilepsy risk levels from EEG signals. J. Chem. Pharm. Sci., 8: 191-194.
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62. Harikumar, R. and M. Balasubramani, 2015. Performance analysis of SVD, ICA and hidden Markov model in classification of epilepsy risk level from EEG signal. Int. J. Applied Eng. Res., 10: 6405-6417.
63. Harikumar, R. and B.V. Kumar, 2015. Performance analysis of neural networks for classification of medical images with wavelets as a feature extractor. Int. J. Imag. Syst. Technol., 25: 33-40.
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64. Harikumar, R. and B.V. Kumar, 2015. Performance analysis of medical image segmentation and edge detection using MEM and PSO algorithms. Applied Math. Inform. Sci., 9: 3235-3243.
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65. Rajaguru, H. and V.K. Bojan, 2014. Performance analysis of EM, SVD and SVM classifiers in classification of carcinogenic regions of medical images. Int. J. Imag. Syst. Technol., 24: 16-22.
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66. Rajaguru, H. and V. Thangavel, 2014. Wavelets and morphological operators based classification of epilepsy risk levels. Math. Problems Eng., Vol. 2014. 10.1155/2014/813197.
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67. Raj, J.S. and R. Harikumar, 2014. A dynamic overlay approach for mobility maintenance in personal communication networks. Peer-to-Peer Networking Applic., 7: 118-128.
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68. Prabhakar, S.K. and H. Rajaguru, 2014. Analysis of PPG signals with respect to SVD, hurst exponent, euclidean distance and k-means clustering. Int. J. Applied Eng. Res., 9: 11793-11797.
69. Prabakaran, A., R. Harikumar, P. Sampath , S. Gandhiraj and K. Silambarasan, 2014. Design and implementation of offset error cancelling using high speed flash ADC. Int. Adv. Res. J. Sci. Eng. Technol., 1: 153-155.
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70. Manjurathi, B., R.H. Kumar and P.N. Kumar, 2014. Test data compression using multiple run length code technique. Int. Rev. Comput. Software, 9: 197-202.
71. Manjurathi, B., R. Harikumar, K.S.G. Kumar and K.T. Jacob, 2014. A test data compression scheme for minimizing test data volume and scan power. J. Theor. Applied Inform. Technol., 62: 634-642.
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72. Manimekalai, P., R. Harikumar and S. Raghavan, 2014. A hybrid maximum power point tracking (MPPT) with interleaved converter for standalone photo voltaic (PV) power generation system. Int. Energy J., 14: 143-154.
73. Jothi, M., N.B. Balamurugan and R. Harikumar, 2014. Design and implementation of VLSI fuzzy classifier for biomedical application. Int. J. Innov. Res. Sci. Eng. Technol., 3: 2641-2648.
74. Harikumar, R., S.N. Shivappriya and S. Raghavan, 2014. Comparison of different optimization algorithms for cardiac arrhythmia classification. Information, 17: 3859-3866.
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75. Harikumar, R., S.N. Shivappriya and R. Janani, 2014. Evaluation of wavelets and classifiers in classifying cardiovascular disorders using wavelet transform. Int. J. Comput. Intell. Inform., 4: 145-154.
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76. Harikumar, R., R.S. Hemanth and B.V. Kumar, 2014. Wavelet neural network as a classifier for medical diagnosis-a review. Int. J. Scient. Res. Comput. Sci. Applic. Manage. Stud., 3: 61-64.
77. Harikumar, R. and T. Vijayakumar, 2014. Performance analysis of wavelet transforms and morphological operator-based classification of epilepsy risk levels. EURASIP J. Adv. Signal Process., Vol. 2014. 10.1186/1687-6180-2014-59.
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78. Harikumar, R. and S.N. Shivappriya, 2014. Intelligent telemetry system for ECG. Indian Heart J., 66: S143-S143.
79. Harikumar, R. and J.S. Raj, 2014. Ad hoc node connectivity improvement analysis-why not through mesh clients? Comput. Electr. Eng., 40: 473-483.
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80. Balasubramani, M., R. Harikumar, C. Ganeshbabu and G.A. Nivhedhitha, 2014. Performance analysis of extreme learning machine for robust classification of epilepsy detection from EEG signals. Information, 17: 1313-1324.
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81. Rajaguru, H., V.K. Bojan and G.B. Chidhambaram, 2013. Adaptive Modulation Techniques and Coding Rate for OFDM Systems. Lambert Academic Publishing, Germany, ISBN-13: 978-3659486517, Pages: 68.
82. Raj, J.S. and R.H. Kumar, 2013. A self organized structure for mobility management in unstable networks. ERES Int. J. Comput. Networks, 1: 7-11.
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83. Raj, J.S. and R. Harikumar, 2013. A localized computing approach for connectivity improvement analysis in wireless personal networks. Wireless Personal Commun., 72: 2867-2883.
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84. Raj, J.S. and R. Harikumar, 2013. A neighbor-aware connectivity architecture for mobile internet maintenance. Smart Comput. Rev., 3: 62-73.
85. Manimekalai, P., R. Harikumar and S. Raghavan, 2013. Evaluating the effect of interleaving and maximum power point tracking (MPPT) in boost converter for photovoltaic (PV) power generation system using MATLAB. Int. J. Simul. Syst. Sci. Technol., 14: 50-57.
86. Manimekalai, P. and R. Harikumar, 2013. Analysis of soft switching interleaved boost converters for photovoltaic (PV) systems using MATLAB simulation. Int. Rev. Model. Simul., 6: 311-316.
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87. Kannan, S., R. Harikumar, K. Paramasivam and N. Viswanathan, 2013. Simulation and evaluation, performance and cost metrics of 3D NOC architecture. Int. J. Energy Syst. Comput. Control, 4: 65-74.
88. Harivikram, T.S., R. Harikumar, C.G. Babu and P. Murugamanickam, 2013. Adaptive modulation and coding rate for OFDM systems. Int. J. Emerg. Technol. Adv. Eng., 3: 250-255.
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89. Harikumar, R., T. Vijayakumar and R. Kasthuri, 2013. Analysis of PSO and hybrid PSO in calculation of epileptic risk level in EEG. Int. J. Soft Comput. Eng., 3: 154-159.
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90. Harikumar, R., R. Prabu and S. Raghavan, 2013. Electrical impedance tomography (EIT) and its medical applications: A review. Int. J. Soft Comput. Eng., 3: 193-198.
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91. Harikumar, R., M. Balasubramani and S. Saravanan, 2013. FPGA implementation of wavelet neural network for epilepsy detection. Int. J. Eng. Innov. Technol., 2: 50-55.
92. Harikumar, R., M. Balasubramani and C.G. Babu, 2013. Performance analysis of SVD, PCA, ICA, hidden markov model in classification of epilepsy risk level from EEG signal. Pensee J., 75: 279-291.
93. Harikumar, R., M. Balasubramani and C.G. Babu, 2013. FPGA implementation of wavelet neural network for epileptic seizure detection. IEICE Electron. Express, 10: 1-6.
94. Harikumar, R., B.V. Kumar, K. Karthick, L.K. Chand and C.N. Kumar, 2013. Baysian imaging concepts for smart fracture detection in x-ray images. Int. J. Electron. Commun. Comput. Technol., 3: 347-351.
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95. Harikumar, R. and T. Vijayakumar, 2013. A comparison of elman and radial basis function (RBF) neural networks in optimization of fuzzy outputs for epilepsy risk levels classification from EEG signals. Int. J. Soft Comput. Eng., 2: 295-303.
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96. Harikumar, R. and M. Balasubramani, 2013. FPGA synthesis of fuzzy based simple traffic controller. Int. J. Adv. Res. Comput. Commun. Eng., 2: 2497-2502.
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97. Harikumar, R. and B.V. Kumar, 2013. Comprehensive analysis of LPG‐PCA algorithms in denoising and deblurring of medical images. Int. J. Imag. Syst. Technol., 23: 157-170.
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98. Sampath, P., R. Harikumar and K. Gunavathi, 2012. CMOS 2nd order Gm-C intermediate frequency band pass filters for wireless systems. Electr. Eng., 222: 237-244.
99. Rajaguru, H., V.K. Bojan and V. Thangavel, 2012. Estimation of Drowsiness from EEG Signals: Estimation of Drowsiness from EEG Signals-A Correlation Dimension Approach. Lambert Academic Publishing, Germany, ISBN-13: 978-3659120190, Pages: 56.
100. Rajaguru, H., V. Thangavel and V.K. Bojan, 2012. Fuzzy Genetic Algorithms, SVM Methods for Epilepsy Classification. Lambert Academic Publishing, Germany, ISBN-13: 978-3659133244, Pages: 116.
101. Rajaguru, H., G.B. Chidambaram and V.K. Bojan, 2012. FPGA Fuzzy (PD & PID) Controller Models for Insulin Pumps in Diabetes: FPGA Implementation of Fuzzy (PD & PID) Controller for Insulin Pumps in Diabetes. Lambert Academic Publishing, Germany, ISBN-13: 978-3659141287, Pages: 76.
102. Rajaguru, H. and V.K. Bojan, 2012. Analysis of Quality Measures for Medical Image Segmentation. Lambert Academic Publishing, Germany, ISBN: 978-3-659-11412-0, Pages: 56.
103. Raj, J.S. and R. Harikumar, 2012. A new distributed architecture for connectivity analysis in wireless networks. Proc. Eng., 30: 394-401.
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104. Manimekalai, P., R. Harikumar and S. Raghavan, 2012. Comparison of photo voltaic (PV) panels and soft switching boost converters for PV power generation systems. Int. Energy J., 13: 201-212.
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105. Kumar, R.H., C. Ganeshbabu, P. Sampath and M. Ramkumar, 2012. Performance analysis of an activity based measurement of blood flow using impedance plethysmography. Electr. Eng., 222: 35-46.
106. Kumar, R.H., B.V. Kumar and S. Gowthami, 2012. Performance evaluation of LPG-PCA algorithm in deblurring of CT and MRI images. Int. J. Comput. Applic., 60: 28-33.
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107. Kumar, R.H. and S.N. Shivappriya, 2012. A novel approach for different morphological characterization of ECG signal. Electr. Eng., 221: 13-24.
108. Kumar , R.H., C. Ganeshbabu and M.R. Kumar, 2012. A novel method for blood flow measurement using plethysmography. Karpagam J. Comput. Sci., 6: 237-245.
109. Karthick, G., R. Harikumar and B.V. Kumar, 2012. Quality measurement in segmentation of medical images. Int. J. Electron. Commun. Comput. Eng., 3: 20-28.
110. Harikumar, R., T. Vijayakumar, C.G. Babu and M.G. Sreejith, 2012. Performance analysis of wavelet transforms and principal components as post classifier for the classification of epilepsy risk levels from EEG signals. Electr. Eng., 221: 25-36.
111. Harikumar, R., T. Vijayakumar, C.G. Babu and M.G. Sreejith, 2012. Performance analysis of morphological operators based feature extraction and SVD, neural networks as post classifier for the classification of epilepsy risk levels. Electr. Eng., 221: 1-12.
112. Harikumar, R., T. Vijayakumar and R. Kasthuri, 2012. Performance analysis of particle swarm optimization technique for classification of epileptic risk level from EEG signals. J. Microeng. Nanoelectron., 3: 69-74.
113. Harikumar, R., N.B. Balamurugan and M. Jothi, 2012. FPGA synthesis of SIRM fuzzy system-classification of diabetic epilepsy risk levels from EEG signal parameters and CBF. Electr. Eng., 221: 313-322.
114. Harikumar, R., M. Balasubramani and T. Vijayakumar, 2012. Performance analysis of patient specific epilepsy risk level classifications from EEG signals using two tier hybrid (fuzzy, soft decision trees models and MLP neural networks) classifiers. Int. J. Soft Comput. Eng., 2: 541-549.
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115. Harikumar, R., C.G. Babu, M. Balasubramani and P. Sinthiya, 2012. Analysis of SVD neural networks for classification of epilepsy risk level from EEG signals. Electr. Eng., 222: 27-34.
116. Harikumar, R., C.G. Babu and P. Shrivignesh, 2012. Earlier detection of oral cancer from fuzzy based photo plethysmography. Int. J. Soft Comput. Eng., 2: 128-133.
117. Harikumar, R., C. GaneshBabu and T. Vijayakumar, 2012. Performance analysis of Elman neural networks as post classifiers for wavelet transforms based feature extraction using hard and soft thresholding methods in the classification of epilepsy risk levels from EEG signals. Eur. J. Sci. Res., 71: 221-232.
118. Harikumar, R., B.V. Kumar, K. Karthik, J.L.K. Chand and C.N. Kumar, 2012. Performance analysis of singular value decomposition (SVD) and radial basis function (RBF) neural networks for epilepsy risk levels classifications from EEG signals. Int. J. Soft Comput. Eng., 2: 232-236.
119. Harikumar, R., B.V. Kumar, G. Karthick, L.K. Chand and C.N. Kumar, 2012. Hierarchical clustering algorithm for intensity based cluster merging and edge detection in medical images. Electr. Eng., 221: 323-338.
120. Harikumar, R., B.V. Kumar, G. Karthick and I.N. Sneddon, 2012. Performance analysis for quality measures using K means clustering and EM models in segmentation of medical images. Int. J. Soft Comput. Eng., 1: 74-80.
121. Harikumar, R. and T. Vijayakumar, 2012. Comprehensive analysis of hierarchical aggregation functions decision trees, SVD, K-means clustering, PCA and rule based AI optimization in the classification of fuzzy based epilepsy risk levels from EEG signals. Int. J. Comput. Inform. Syst. Ind. Manage. Applic., 5: 260-268.
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122. HariKumar, R., V.K. Sudhaman and C.G. Babu, 2012. FPGA synthesis of fuzzy (PD and PID) controller for insulin pumps in diabetes using cadence. Int. J. Soft Comput. Eng., 1: 324-331.
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123. HariKumar, R., T. Vijayakumar and M.G. Sreejith, 2012. Comprehensive analysis of hierarchical aggregation functions decision trees and minimum relative entropy as post classifiers in the classification of fuzzy based epilepsy risk levels. Int. J. Soft Comput. Eng., 2: 148-154.
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124. HariKumar, R., N.S. Vasanthi and M. Balasubramani, 2012. Performance analysis of artificial neural networks and statistical methods in classification of oral and breast cancer stages. Int. J. Soft Comput. Eng., 2: 263-269.
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125. Balamurugan, N.B., M. Jothi and R. Harikumar, 2012. FPGA synthesis of SIRM fuzzy system-classification of diabetic epilepsy risk level. Proc. Eng., 38: 391-404.
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126. Sukanesh, R. and R. Harikumar, 2011. Analysis of photo-plethysmography (PPG) signals with motion artifacts (gaussian noise) using wavelet transforms. Biomed. Fuzzy Hum. Sci.: Official J. Biomed. Fuzzy Syst. Assoc., 16: 135-139.
127. Raj, J.S. and R. Harikumar, 2011. A review on localized topology control approaches in wireless network. Int. J. Comput. Sci. Inform. Eng., 2: 85-91.
128. Harikumar, R., T. Vijayakumar and C. Palanisamy, 2011. Performance analysis of wavelet transforms and elman neural networks for the classification of epilepsy risk levels from EEG signals. Int. J. Neural Networks Applic., 4: 61-67.
129. Harikumar, R., C. Palanisamy and T. Vijayakumar, 2011. Performance analysis of fuzzy soft decision trees models and support vector machines for epilepsy risk level classifications from EEG signal parameters. Int. J. Biosignal Process., 2: 61-68.
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130. Harikumar, R., A. Shanmugam and V.K. Sudhaman, 2011. FPGA implementation of fuzzy (PD and PID) controller for insulin pumps in diabetes. AMSE J. Modeling C, 66: 50-63.
131. Harikumar, R. and S.N. Shivappriya, 2011. Analysis of QRS detection algorithm for cardiac abnormalities-a review. Int. J. Soft Comput. Eng., 1: 80-88.
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132. Harikumar, R. and S. Arun, 2011. Analysis of an edge preserving denoising technique for X-ray and ultrasonic images using wavelet transform. Int. J. Inform. Anal. Process., 4: 23-26.
133. Harikumar, R. and M. Balasubramani, 2011. FPGA synthesis of soft decision tree (SDT) for classification of epilepsy risk levels from fuzzy based classifier using EEG signals. Int. J. Soft Comput. Eng., 1: 206-211.
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134. HariKumar, R. and T.V. Kumar, 2011. Performance analysis of soft decision trees models for fuzzy based classification of epilepsy risk levels from EEG signals. Int. J. Soft Comput. Eng., 1: 21-27.
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135. HariKumar, R. and T.V. Kumar, 2011. Estimation of drowsiness and classification of epilepsy risk levels from EEG signals using chaos theory. Int. J. Soft Comput. Eng., 1: 60-65.
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136. Sukanesh, R., R. Harikumar and A. Shanmugam, 2009. FPGA synthesis of heterogeneous and SIRM fuzzy system for classification of diabetic epilepsy risk levels, I.E. India J. Interdisciplinary Panels, 90: 20-25.
137. Harikumar, R. and R. Sukanesh, 2009. A comparison of Soft (min-max) Decision trees and hierarchical decision trees for patient specific fuzzy classifier in the classification of epilepsy risk levels from EEG signals. AMSE J. Modell. C, 70: 18-38.
138. HariKumar, R. and T. Vijayakumar, 2009. Performance analysis of patient specific elman-chaotic optimization model for fuzzy based epilepsy risk level classification from EEG signals. Int. J. Smart Sens. Intell. Syst., 2: 612-635.
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139. HariKumar, R. and N.S. Vasanthi, 2009. Performance analysis of artificial neural networks in classification of oral cancer stages. Lectures Modell. Simulation Trivandrum India, 10: 94-101.
140. Sukanesh, R. and R. HariKumar, 2008. Pattern recognition and classification for medical diagnosis from bio-signals-a review, I.E. India J. Interdisciplinary Panels, 89: 24-32.
141. Sukanesh, R. and R. HariKumar, 2008. A comprehensive analysis on post processing mathematical models (MRE, aggregation operators and soft decision trees) for patient specific fuzzy based epilepsy risk level classifier from EEG signals, I.E. India J. Interdisciplinary Panels, 89: 3-12.
142. Sukanesh, R., R. Harikumar, N.S. Balaji and S.R. Balasubramaniam, 2007. Analysis of image compression by Minimum Relative Entropy (MRE) and restoration through weighted region growing techniques for medical images. Eng. Lett., 14: 84-89.
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143. Sukanesh, R. and R. Harikumar, 2007. Performance analysis of different fuzzy techniques in classification of epilepsy risk level for diabetic patients using cerebral blood flow, aggregation operators and EEG signals. IE India J. Interdisciplinary Panels, 88: 12-20.
144. Sukanesh, R. and R. Harikumar, 2007. Fuzzy techniques and neural networks (RBF) for classification of epilepsy risk levels from EEG signals. Biomed. Fuzzy Hum. Sci.: Official J. Biomed. Fuzzy Syst. Assoc., 12: 17-21.
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145. Sukanesh, R. and R. Harikumar, 2007. Diagnosis and classification of epilepsy risk levels from EEG signals using fuzzy aggregation techniques. Eng. Lett., 14: 90-95.
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146. Sukanesh, R. and R. Harikumar, 2007. Analysis of fuzzy techniques and neural networks (rbf&mlp) in classification of epilepsy risk levels from EEG signals. IETE J. Res., 53: 465-474.
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147. Sukanesh, R. and R. Harikumar, 2007. A comparison of genetic algorithm and neural network (MLP) in patient specific classification of epilepsy risk levels from EEG signals. Eng. Lett., 14: 96-104.
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148. Sukanesh, R. and R. Harikumar, 2006. Analysis of SIRM fuzzy systems in classification of epilepsy risk levels for diabetic neuropathy patients using cerebral blood flow and EEG signals. India J. Interdisciplinary Panels, 87: 33-36.
149. Sukanesh, R. and R. Harikumar, 2006. A simple recurrent supervised learning neural network for classification of epilepsy risk levels from EEG signals. IE India J. Interdisciplinary Panels, 87: 37-43.
150. Sukanesh, R. and R. Harikumar, 2006. A patient specific neural networks (MLP) for optimization of fuzzy outputs in classification of epilepsy risk levels from EEG signals. Eng. Lett., 13: 50-56.
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151. Harikumar, R. and R. Sukanesh, 2006. A comparison of Elman and MLP feed forward neural networks for classification of epilepsy risk level using EEG signals. AMSE J. Modell., 67: 43-60.
152. Kumar, R.H. and R. Sukanesh, 2005. Fuzzy techniques with aggregation operators for classification and optimization of epilepsy risk level from EEG signals. IETE J. Res., 51: 379-388.
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153. Harikumar, R., R. Sukanesh and P.A. Bharathi, 2005. Genetic algorithm optimization of fuzzy outputs for classification of epilepsy risk levels from EEG signals. IE India J. Interdisciplinary Panels, 86: 9-17.
154. Harikumar, R., R. Sukanesh and B.S. Narayan, 2005. Fuzzy techniques and fuzzy aggregation operators for classification of epilepsy risk level using EEG signal parameters. AMSE J. Modell., 66: 43-63.
155. Harikumar, R. and R. Sukanesh, 2005. Fuzzy techniques and statistical tests for epilepsy risk level classification using EEG signals. IE India J. Interdisciplinary Panels, 86: 29-36.
156. Paramasivam, K., R. Harikumar and R. Sundararajan, 2004. Simulation of VLSI design using parallel architecture for epilepsy risk level diagnosis in diabetic neuropathy. IETE J. Res., 50: 297-304.
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157. Harikumar, R. and S. Selvan, 2002. Fuzzy based classification of patient state in diabetic neuropathy using cerebral blood flow. J. Syst. Soc. India Paritantra, 7: 37-41.