Qualification: 
Ph.D, M.Tech
Email: 
r_ramanathan@cb.amrita.edu

Dr. R. Ramanathan joined the Department of Electronics and Communication Engineering, Amrita Vishwa Vidyapeetham in the year 2006, where he is currently an Assistant Professor (Selection Grade). He received his B.E. degree in Electronics and Communication from Bharathiyar University, Coimbatore, India in 2004. He received his M.Tech degree in Computational Engineering and Networking and Ph. D. degree in Electronics and Communication from Amrita Vishwa Vidyapeetham, Coimbatore, India in 2011 and 2015 respectively.  Dr. Ramanathan is the recipient of Best Outgoing Student in High School in 2000 and Best Outgoing Student in college (undergraduate level) in 2004. Prior to joining Amrita, he was working as Senior Engineer – Transmissions for Nokia projects in Hutch Essar ./ Vodafone for two years.

His areas of research include optimization and signal processing for wireless communication and networks, MIMO and OFDM communications, Bio-inspired Computing, Wireless Sensor Networks, Physical layer signal design and security and Convex Optimization. He has authored around 26 technical papers in reputed conferences and journals indexed in Scopus. He has coauthored a book “Digital Signal and Image Processing- The Sparse way” published by Elsevier India in 2012.

He is a member of Institution of Electronics and Telecommunication Engineers (IETE) and Association of Communication, Electrical and Electronics Engineers (ACEEE). He is the reviewer for the journals IET Signal Processing, IET Communications and Wiley Computer Applications in Engineering Education.

 Research Expertise

  •  Physical Layer Security in Energy Harvesting Wireless Networks
  •  Device free localization in Wireless Sensor Networks
  •  Compressed Sensing in Massive MIMO systems
  •  Localization in 3D Wireless Sensor Networks
  •  Design and development of Protocols in Energy Harvesting Wireless Networks
  •  MIMO Radar Signal Processing
  •  Full Duplex D2D communication
  •  Massive 5G wireless communication systems
  •  Vehicular Networks and Communications

 

 Teaching

  •  Wireless Communication & Networks
  •  Mathematical Methods for Communication Engineering
  •  Digital Communication
  •  Convex Optimization
  •  MIMO and Multicarrier Communications
  •  Signal Processing
     

Publications

Publication Type: Journal Article

Year of Conference Publication Type Title

2017

Journal Article

Dr. Ramanathan R. and Dr. Jayakumar M., “A Support Vector Regression Approach to Detection in Large-MIMO Systems”, Telecommunication Systems, vol. 64, no. 4, pp. 709 - 717, 2017.[Abstract]


We propose a support vector regression approach for symbol detection in large-MIMO systems employing spatial multiplexing. We explore the applicability of machine learning algorithms, in particular support vector machines, to address one of the recent research problem in communications.The machine learning capability is exploited to achieve fast detection in large dimension systems. The performance of the proposed method is compared with lattice reduction aided detection which is currently the popular choice and the improvement in terms of bit error rate is demonstrated. The sparse formulation of the problem matrix reduces the computational complexity and enables faster detection. The proposed detection algorithm is tailored to address both uncorrelated and correlated channel conditions as well.

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2016

Journal Article

Dr. Ramanathan R. and Dr. Jayakumar M., “A Low Complex Sparse Formulation of Semidefinite Relaxation Detector for Large-MIMO Systems Employing BPSK Constellations”, Wireless Personal Communications, vol. 90, pp. 1317–1329, 2016.[Abstract]


Semidefinite relaxation detector is a promising approach to large-MIMO detection but for its computational complexity. The major computational cost is incurred in solving the semidefinite program (SDP). In this paper, we propose a sparse semidefinite relaxation (S-SDR) detector by reformulating the SDP problem thereby reducing the computational complexity. We formulate the system model using a sparse approach and further introduce a regularization term inducing sparsity into the semidefinite programming model. We provide a sparse formulation requiring approximately 50 % of the computations compared to the conventional semidefinite programming approach. We apply the proposed semidefinite relaxation detector in large-MIMO channels upto 100×100 systems and compare its BER performance and complexity. We observe that the BER performance is similar to the conventional semidefinite relaxation with the proposed S-SDR detector requiring relatively fewer computations.

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2015

Journal Article

Dr. Ramanathan R. and Dr. Jayakumar M., “A Performance Study of Semidefinite Relaxation Detector in Spatially Correlated and Rank Deficient Large MIMO Systems”, Wireless Personal Communications, vol. 83, pp. 2883-2897, 2015.[Abstract]


Large MIMO detection has gained significant attention in the recent past with computational complexity as the research focus. However, they assume the channel to be i.i.d and uncorrelated, which is not a valid assumption in practice due to the fixed physical space constraints in large MIMO. Nevertheless, there is a little work carried out in these lines. In this paper, we consider the problem of detection in large spatial multiplexing MIMO systems and we investigate the semidefinite relaxation (SDR) approach to solve this problem. We investigate the applicability of SDR approach in large MIMO setting and study its performance in spatially correlated and rank deficient channel conditions. Through the simulation results, we demonstrate the superior performance of semidefinite relaxation detector over other existing methods in uncorrelated and correlated large MIMO systems especially in low SNR regime. The performance of SDR detector is noteworthy with large number of antennas despite the system being rank deficient and the average running time also scales up well for large systems. © 2015, Springer Science+Business Media New York.

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2015

Journal Article

Dr. Ramanathan R. and Dr. Jayakumar M., “A novel cuckoo search approach to detection in spatially correlated MIMO channels”, International Journal of Mathematical Modelling and Numerical Optimisation, vol. 6, no. 2, pp. 101-113, 2015.[Abstract]


In this paper, we propose a cuckoo search approach to detect the transmitted symbols in spatially correlated multiple input multiple output (MIMO) channels. Detection is considered to be a challenging task in correlated channels due to the fact that the channel matrix tends to be ill conditioned or sometimes rank deficient. Currently, lattice reduction aided detection is understood to be the best approach for detection in spatially correlated channels. We propose cuckoo search as an effective approach to solve this problem. We provide the performance comparison of the proposed detector with various other detectors including lattice reduction aided detector. Through the results, we demonstrate the efficiency of cuckoo search detector over other detectors in uncorrelated and correlated channels as well. We corroborate that cuckoo search detector is a better choice over other existing detectors especially in spatially correlated MIMO channels.

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2015

Journal Article

S. M. and Dr. Ramanathan R., “Performance evaluation of DWT based multicarrier systems over frequency selective channels”, International Journal of Engineering and Technology, vol. 7, pp. 1651-1658, 2015.[Abstract]


In this work, the performance of DWT based OFDM is studied and compared it with conventional FFT based OFDM over frequency selective channels in different test environments. The Bit Error Rate (BER) estimation is done to evaluate the performance of both the systems. In DWT based OFDM, different wavelet families such as haar, daubechies, coiflet and biorthogonal were used with different levels of decomposition. The simulation results show that in all channels, DWT based OFDM requires less SNR value to achieve the minimum BER of 10-3, when compared to conventional FFT based OFDM. Therefore, DWT based OFDM can be used in place of FFT based OFDM with high bandwidth efficiency.

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2015

Journal Article

K. M.S., S., P., and Dr. Ramanathan R., “Performance evaluation of DWT based multicarrier system in time varying channels”, International Journal of Engineering and Technology, vol. 7, pp. 1633-1641, 2015.[Abstract]


With an increase in user mobility, data rate and carrier frequencies we have to consider time variant channels. In order to overcome the impairments of the time varying channel on conventional OFDM system, a wavelet based OFDM system is investigated in place of FFT based system and its BER performance is analyzed for different Doppler frequencies. The results show that DWT based OFDM gives better performance compared to conventional OFDM system.

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2015

Journal Article

N. S., S., T., and Dr. Ramanathan R., “Investigation of PAPR in discrete wavelet transform based multi-carrier systems”, International Journal of Engineering and Technology, vol. 7, pp. 1625-1632, 2015.[Abstract]


The objective of the paper is to formulate a measure to reduce PAPR problem in Orthogonal Frequency Division Multiplexing. To mitigate the problem of PAPR, a Discrete Wavelet Transform based system is employed instead of conventional OFDM. For the comparative study, the PAPR in conventional OFDM is analyzed for varying number of subcarriers and for different channel taps. The result of conventional OFDM is compared with wavelet based OFDM, employing wavelets namely - 'Haar', 'Daubechies', 'Symlets' and 'Biorthogonal' wavelets. Further the PAPR is analyzed for varying levels and different length of channel impulse response. The simulation results show that wavelet based OFDM has less PAPR than conventional OFDM. With the increase in the number level, the PAPR at the demodulator side decreases in the wavelet based OFDM.

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2010

Journal Article

Dr. Ramanathan R., Dr. Soman K. P., and , “A Novel Methodology for Designing Linear Phase IIR Filters”, Aceee International Journal on Communication, vol. 1, 2010.[Abstract]


This paper presents a novel technique for designing an Infinite Impulse Response (IIR) Filter with Linear Phase Response. The design of IIR filter is always a challenging task due to the reason that a Linear Phase Response is not realizable in this kind. The conventional techniques involve large number of samples and higher order filter for better approximation resulting in complex hardware for implementing the same. In addition, an extensive computational resource for obtaining the inverse of huge matrices is required... More »»

Publication Type: Conference Paper

Year of Conference Publication Type Title

2015

Conference Paper

I. Aravindan, K. Antony, R., K. Kumar, A., Snehith, T. C., Padmakumar, A., and Dr. Ramanathan R., “A performance study of MIMO detectors in the presence of channel estimation errors”, in Proceedings - 2015 International Conference on Communication, Information and Computing Technology, ICCICT 2015, 2015.[Abstract]


In this paper, we investigate the performance of the low-complexity algorithms based on Likelihood Ascent Search (LAS) and Tabu Search (TS) for detection in MIMO systems with channel estimation errors. Here, we briefly review the algorithms for LAS and TS and their variants and subsequently compare them for various MIMO settings. We provide the simulation results for BER performance in 2× 2, 4× 4 and 8× 8 MIMO systems. From the results, we conclude that Tabu Search shows no degradation in BER up to an estimation error variance of 0.05 in lower order systems, while LAS offers the same advantage in higher order systems. However, this trend is also valid for LAS in lower order systems, in the low SNR regime. We corroborate that LAS and TS are worthy candidates for further research. © 2015 IEEE.

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2015

Conference Paper

K. K. Anil, Raju, A. K., Snehith, T. C., and Dr. Ramanathan R., “Likelihood Ascent-Gibbs Sampling for efficient MIMO detection”, in Advance Computing Conference (IACC), 2015 IEEE International, 2015.[Abstract]


In this paper, we propose a hybridized Likelihood Ascent-Mixed Gibbs Sampling (LAS-MGS) for effective detection with channel estimation error. We analyze its performance in the presence of channel estimation error for 2×2 and 4×4 MIMO systems employing BPSK modulation scheme. At low SNRs, performance of ZF-MGS and LAS-MGS is similar but at high SNRs, LAS-MGS performs significantly better. LAS-MGS outperforms conventional Mixed Gibbs Sampling (MGS) and we are able to harness similar gain even with channel estimation errors. We conclude that LAS-MGS is a worthy candidate for further research.

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2015

Conference Paper

T. C. Snehith, Anil, K. K., Raju, A. K., and Dr. Ramanathan R., “Impact of channel estimation errors on lattice reduction gains in MIMO systems”, in Advance Computing Conference (IACC), 2015 IEEE International, 2015.[Abstract]


In this paper, we propose an approach based on Lattice Reduction (LR) algorithm which preserves the channel norm in the presence of estimation errors. We analyze the channel norm of perfect and imperfect channel by employing LR algorithm on both perfect and imperfect channels in MIMO systems with 2, 4, 8 and 16 antennas for various error variances. We conclude that effective detection can be achieved even with imperfect channel by employing LR on those channels.

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2011

Conference Paper

A. Chandran, R. Karthik, A., Kumar, A., M. Siva, S., Iyer, U. S., Dr. Ramanathan R., and Naidu, R. C., “Discrete wavelet transform based spectrum sensing in futuristic cognitive radios”, in 2011 International Conference on Devices and Communications, ICDeCom 2011 - Proceedings, Mesra, 2011.[Abstract]


With the advent of an era of wireless communication, the number of users is on the rise, the result of which is spectral congestion. Cognitive Radio systems provide an intelligent and an attractive solution to this technical crisis. Spectrum Sensing is indispensable for the functioning of Cognitive Radio and helps in efficient spectrum utilization. In this paper, a wavelet based approach to spectrum sensing is dealt with. Wavelets provide a new dimension to tackle spectrum sensing. This method is comparatively easier and more reliable than the conventional energy detector. An algorithm for spectrum sensing has been proposed and the results obtained for various scenarios are tabulated. A comparison with the conventional energy detector has been performed to substantiate the proposal. Some important conditions are also specified. © 2011 IEEE. More »»

2011

Conference Paper

N. Ashish, Srivatsan, K. R. Atul, Karthikeyan, N., Pasupuleti, R. T., Gutta, S., Raman, A. A., and Dr. Ramanathan R., “A novel channel estimation technique for MIMO-OFDM systems for frequency selective rayleigh channel”, in 2011 International Conference on Devices and Communications, ICDeCom 2011 - Proceedings, Mesra, 2011.[Abstract]


The MIMO system convincingly promises a better bit rate in comparison with a SISO system. The system gets even efficient when OFDM is amalgamated with MIMO to obtain better data rates even in hostile channel environment. Research establishes OFDM as a potential candidate for use in MIMO systems for the reasons like inherent FFT, waveform adaptation, advanced antenna techniques, multiple access, interoperability, etc. Since, channel estimation is an integral part of OFDM system; it stands to demand a technique that can offer accurate channel characterization for effective equalization to follow. In addition, there exists a tradeoff between accuracy of estimation and complexity of the technique. In this paper, a combined channel estimation technique, which combines the virtues of Least Squares and LMMSE estimators with SVD in MIMO-OFDM systems. This combined strategy increases the estimate accuracy without much increase in complexity or computation considering a Rayleigh frequency-selective channel environment. The proposed technique is explicated with necessary mathematics and the theory is well substantiated with simulations. The technique is fitted into the OFDM framework and the simulation results indicate a good estimate of the channel. The theory and results are presented and discussed in the paper. © 2011 IEEE. More »»

2011

Conference Paper

A. Chandran, R. Karthik, A., Kumar, A., Naidu, R. C., M. Siva, S., Iyer, U. S., and Dr. Ramanathan R., “A novel spectrum sensing technique for low Signal to Noise Ratio conditions”, in 2011 International Conference on Emerging Trends in Electrical and Computer Technology, ICETECT 2011, Chunkankadai, 2011, pp. 681-685.[Abstract]


Wireless communication is an emerging and evergreen field of research and will continue to be so in the future. Increased demands in spectrum and users eventually result in spectral congestion. Cognitive Radio systems provide an intelligent and an attractive solution to this problem. Spectrum Sensing is the main key for the functioning of Cognitive Radio and helps in efficient spectrum utilization. Wavelets provide a new dimension to tackle spectrum sensing when compared to the conventional methods. In real time applications, loss of signal is prominent in low SNR conditions and hence a system capable of working under such conditions will prove to be an asset. In this paper, a wavelet based approach to spectrum sensing at low SNRs is dealt with. A new algorithm for spectrum sensing has been proposed here which emphasizes more on the functioning of systems in low SNR conditions. © 2011 IEEE. More »»

2011

Conference Paper

N. Ashish, Srivatsan, K. R. Atul, Karthikeyan, N., Pasupuleti, R. T., Gutta, S., Raman, A. A., and Dr. Ramanathan R., “A novel channel estimation technique for MIMO-OFDM systems for Frequency Selective Ricean channel”, in 2011 International Conference on Emerging Trends in Electrical and Computer Technology, ICETECT 2011, Chunkankadai, 2011, pp. 671-675.[Abstract]


The MIMO system convincingly promises a better bit rate in comparison with a SISO system. The system gets even efficient when OFDM is implemented with MIMO to obtain better data rates even in hostile channel environment. Research establishes OFDM as a potential candidate for use in MIMO systems for the reasons like inherent FFT, waveform adaptation, advanced antenna techniques, multiple access, interoperability, etc. Since, channel estimation is an integral part of OFDM system; it stands to demand a technique that can offer accurate channel characterization for effective equalization to follow. In addition, there exists a tradeoff between accuracy of estimation and complexity of the technique. In this paper, a combined channel estimation technique, which combines the virtues of Least Squares and LMMSE estimators with SVD in MIMO-OFDM systems. This combined strategy increases the estimate accuracy without much increase in complexity or computation considering a Ricean Frequency Selective channel environment. The proposed technique is explicated with necessary mathematics and the theory is well substantiated with simulations. The technique is fitted into the OFDM framework and the simulation results indicate a good estimate of the channel. The theory and results are presented and discussed in the paper. © 2011 IEEE. More »»

2010

Conference Paper

C. Manoj, Narayanan, K. A., Kota, B. A., Shivaram, P. A., Prasad, A. S., and Dr. Ramanathan R., “Investigation of various channel models for application of constant power water filling algorithm”, in 2010 IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2010, Coimbatore, 2010, pp. 581-587.[Abstract]


The increasing demand for portable and mobile communication devices has made wireless communication an indispensable field of research. The performance of any wireless communication system is determined to a large extent by the characteristics of the channel. For the purpose of system design and development, it is advantageous to have knowledge of the characteristics of the channel. In this paper, we discuss the various channel models that are in use today. We also present an overview of the various estimation and equalization algorithms that are widely employed. We then present the results of the simulations of the various channel models, and the observations made from these simulations. Finally, we describe the theory of constant power water filling algorithm and how it can applied to maximize the capacity of a Rayleigh fading channel. © 2010 IEEE. More »»

2010

Conference Paper

A. Chandran, R. Karthik, A., Kumar, A., Naidu, R. C., M. Siva, S., Iyer, U. S., and Dr. Ramanathan R., “Evaluation of energy detector based spectrum sensing for OFDM based cognitive radio”, in Proceedings of 2010 International Conference on Communication and Computational Intelligence, INCOCCI-2010, Perundurai, Erode, 2010, pp. 163-167.[Abstract]


With congested wireless spectrum and increasing number of users, cognitive radio serve as a panacea for efficient spectrum utilization. This stands to substantiate the amount of research happening in this area. Spectrum sensing is indubitably a key functionality in cognitive radio, which helps determining the spectral holes and white spaces for the secondary users to communicate. In this paper, the energy detector based spectrum sensing for OFDM based cognitive radio is studied and evaluated for various Signal and Noise conditions. The threshold which is a determining factor in energy detector is computed using a divide and conquer approach which is also a novelty of this paper. The bound for minimum width of the white space that is detectable by an energy detector in the case of real time multiple primary user scenario is well established through convincing simulations. The influence of SNR on the spectrum sensing is also presented with regard to the accuracy of sensing or probability of detection. Certain indispensable conditions for implementation of this detector are also discussed. © 2010 Kongu Engineering College. More »»

2010

Conference Paper

D. M. Chinnam, Madhusudhan, J., Nandhini, C., Prathyusha, S. N., Sowmiya, S., Dr. Ramanathan R., and Soman, K. P., “Implementation of a low cost synthetic aperture radar using software defined radio”, in 2010 2nd International Conference on Computing, Communication and Networking Technologies, ICCCNT 2010, Karur, 2010.[Abstract]


GNU radio is a free open-source software toolkit for building software radios, in which software defines the transmitted waveforms and demodulates the received waveforms. In this paper an attempt has been made to explore the means to use a Software Defined Radio (SDR) to implement a basic radar system and then synthetic aperture radar. An experiment where in readings at two different scenarios (free environment and metal object) are taken into account and their plots are also given. This has been attempted keeping in mind the exponential increase in chip computing power and the ability to upgrade a radio transceiver via software updates with a marginal investment, the two features which makes such a foray attractive, technology wise and cost wise. This attempt also takes us a step closer to establishing the concept of a Cognitive radar which is software signal processing intensive. ©2010 IEEE. More »»

2010

Conference Paper

D. M. Chinnam, Madhusudhan, J., Nandhini, C., Prathyusha, S. N., Sowmiya, S., Dr. Ramanathan R., and Soman, K. P., “Intrusion detection using software defined noise radar”, in 2010 2nd International Conference on Computing, Communication and Networking Technologies, ICCCNT 2010, Karur, 2010.[Abstract]


The need for reliable systems for detecting intrusions into a given area has given rise to the research and use of random noise radars. This paper deals with the issues regarding the use of such systems. The advantages of the use of such radar are illustrated followed by the actual mode of implementing the system itself. The novelty in this approach is the use a software defined radio as the platform for the system as it has a number of added advantages as have been detailed Subsequently, the intrusion detection can be viewed as a classification problem and solved using any machine learning algorithm. The paper also investigates the use of support vector machines (SVM) for the above said problem and derives a suitable model for classification. The training and testing of SVM model is in progress. ©2010 IEEE. More »»

2009

Conference Paper

Dr. Ramanathan R., Rohini, P. A., Dharshana, G., and Soman, K. P., “Investigation and development of methods to solve multi-class classification problems”, in ARTCom 2009 - International Conference on Advances in Recent Technologies in Communication and Computing, Kottayam, Kerala, 2009.[Abstract]


Most of the classification problems frequently encounter a multi class predicament and offers a good scope for research. This paper has a comprehensive approach to the available multi-class technique using Artificial Neural Networks and then introduces a new algorithm to overcome the demerits of the former. In addition, a new algorithm combining ANN and chameleon clustering is suggested and validated. An SVM model for the above is also proposed and sufficiently tested with a typical example i.e. Image Segmentation. Also, the permutation effects prevailing in Half -against-Half multi class algorithm of SVM is efficiently tackled by developing an algorithm using "circular shift strategy" and employing the same. The use of clustering methods with SVM to improve its efficiency is also discussed. All the above mentioned models are extensively analyzed and the results are presented. It is found that the proposed method is an effective alternative for existing methods and offers consistent performance. © 2009 IEEE. More »»

2009

Conference Paper

Dr. Ramanathan R., Ponmathavan, S., Valliappan, N., Thaneshwaran, L., Nair, A. S., and Soman, K. P., “Optical character recognition for English and Tamil using support vector machines”, in ACT 2009 - International Conference on Advances in Computing, Control and Telecommunication Technologies, Trivandrum, Kerala, 2009.[Abstract]


Optical Character Recognition is an evergreen area of research and is verily used in various real time applications. This paper proposes a new technique of Optical character Recognition using Gabor filters and Support Vector machines (SVM). This method proves to be very effective with the use of Gabor filters for feature extraction and SVM for developing the model. The model proposed is trained and validated for two languages - English and Tamil and the results are found to be very much encouraging. The model developed works for the entire character set in both the languages including symbols and numerals. In addition , the model can recognise the characetrs of six different fonts in English and Twelve different fonts in Tamil. The average accuracy of recognition for English is 97% and for Tamil it is 84%, which is achieved in just three iterations of training. The method can turn out to be a suitable candidate for future applications in this area. © 2009 IEEE. More »»

2009

Conference Paper

Dr. Ramanathan R., Thaneshwaran, L., Viknesh, V., Arunkumar, T., Yuvaraj, P., and Soman, K. P., “A novel technique for english font recognition using support vector machines”, in ARTCom 2009 - International Conference on Advances in Recent Technologies in Communication and Computing, Kottayam, Kerala, 2009.[Abstract]


Font Recognition is one of the Challenging tasks in Optical Character Recognition. Most of the existing methods for font recognition make use of local typographical features and connected component analysis. In this paper, English font recognition is done based on global texture analysis. The main objective of this proposal is to employ support vector machines (SVM) in identifying various fonts. The feature vectors are extracted by making use of Gabor filters and the proposed SVM is trained using these features. The method is found to give superior performance over neural networks by avoiding local minima points. The SVM model is formulated tested and the results are presented in this paper. It is observed that this method is content independent and the SVM classifier shows an average accuracy of 93.54%. © 2009 IEEE. More »»

2009

Conference Paper

Dr. Ramanathan R. and Soman, K. P., “Improved technique for the construction of parametric M - Band wavelets”, in ARTCom 2009 - International Conference on Advances in Recent Technologies in Communication and Computing, Kottayam, Kerala, 2009.[Abstract]


Demanding applications of wavelets in OFDM modulation, Watermarking, cognitive radio and wireless networks has created an immense interest amongst the researchers to work on the design of good wavelet system. Parametric and M-Band wavelets draw a special attention in this category. A commensurate procedure for constructing a superior M-Band Parametric wavelet system is proposed in this paper. The idea of Modulation matrix decomposition and the relation with corresponding Polyphase matrix and its factorization is exploited to possible extent to make the design process plain and easy. The appropriate polynomial matrix is put in place to extend the filter design to any required length. The simple property of the kroneckor product of two matrices is contemplated to achieve M-Band design. This paper ponders on the above-mentioned factors and accomplishes the task of designing an M-Band parametric wavelet, which is complete in itself. Few examples are used to substantiate the proposed method. © 2009 IEEE. More »»

2009

Conference Paper

Dr. Ramanathan R., Nair, A. S., Sagar, V. V., Sriram, N., and Soman, K. P., “A support vector machines approach for efficient facial expression recognition”, in ARTCom 2009 - International Conference on Advances in Recent Technologies in Communication and Computing, Kottayam, Kerala, 2009.[Abstract]


Current scenario in computer vision demands an efficient and robust technique for facial expression recognition. There is also a need for a generalized technique that can even be used for content based image retrieval and analysis. This paper introduces a novel methodology of facial expression recognition using Support Vector Machines. An efficient model is trained and developed using the necessary features extracted by employing 2D Gabor filters. Practically, six different methods for handling the feature vectors are discussed and extensively analyzed in this paper. The developed model is tested and cross validated and the detailed results are presented. It is observed that the proposed method offers a consistent and good accuracy (83.3%) for all the six basic expressions considered. In addition, the implementation complexity is reduced by minimizing the number of support vectors, unlike the traditional counterparts. The proposed method shall definitely turn out to be an effective alternative for the existing methods. © 2009 IEEE. More »»

2009

Conference Paper

Dr. Ramanathan R., Nair, A. S., Thaneshwaran, L., Ponmathavan, S., Valliappan, N., and Soman, K. P., “Robust feature extraction technique for optical character recognition”, in ACT 2009 - International Conference on Advances in Computing, Control and Telecommunication Technologies, Trivandrum, Kerala, 2009.[Abstract]


Optical Character Recognition (OCR) is a classical research field and has become one of most thriving applications in the field of pattern recognition. Feature extraction is a key step in the process of OCR, which in fact is a deciding factor of the accuracy of the system. This paper proposes a novel and robust technique for feature extraction using Gabor Filters, to be employed in the OCR. The use of 2D Gabor filters is investigated and features are extracted using these filters. The technique generally extracts fifty features based on global texture analysis and can be further extended to increase the number of features if necessary. The algorithm is well explained and is found that the proposed method demonstrated better performance in efficiency. In addition, experimental results show that the method gains high recognition rate and cost reasonable average running time. © 2009 IEEE. More »»

2009

Conference Paper

Dr. Ramanathan R., Ponmathavan, S., Thaneshwaran, L., Nair, A. S., Valliappan, N., and Soman, K. P., “Tamil font recognition using gabor filters and support vector machines”, in ACT 2009 - International Conference on Advances in Computing, Control and Telecommunication Technologies, Trivandrum, Kerala, 2009.[Abstract]


Tamil Font Recognition is one of the Challenging tasks in Optical Character Recognition and Document Analysis. Most of the existing methods for font recognition make use of local typographical features and connected component analysis. In this paper, Tamil font recognition is done based on global texture analysis. The main objective of this proposal is to employ support vector machines (SVM) in identifying various fonts in Tamil. The feature vectors are extracted by making use of Gabor filters and the proposed SVM is trained using these features. The method is found to give superior performance over neural networks by avoiding local minima points. The SVM model is formulated tested and the results are presented in this paper. It is observed that this method is content independent and the SVM classifier shows an average accuracy of 92.5%. © 2009 IEEE. More »»

2009

Conference Paper

Dr. Ramanathan R., Valliappan, N., Mathavan, S. P., Gayathri, M., Priya, R., and Soman, K. P., “Generalised and channel independent SVM based robust decoders for wireless applications”, in ARTCom 2009 - International Conference on Advances in Recent Technologies in Communication and Computing, Kottayam, Kerala, 2009.[Abstract]


Emerging applications in wireless communications and Software Defined Radio require robust and generalized decoders with a very good efficiency. This paper aims at introducing a novel and powerful method of implementing a decoder using Support Vector Machines (SVM) to exhibit good performance irrespective of the channel model. The method proposed also ensures a generalization in the design of decoder, which can be easily adaptable for any type of coding technique used. In addition, this method overcomes the demerits of the traditional decoders like Viterbi and other decoders using Neural Networks. The error correction codes like Hamming and Convolutional codes are considered for experimentation. Using SVM, which is a class of machine learning algorithm, this process is viewed as a multi-class classification problem and error correction is achieved in a simpler way. An extensive analysis with regard to the effect of channel and modulation techniques is also made and presented. The proposed SVM model is sufficiently cross validated and found to be an effective replacement for the existing counterparts. © 2009 IEEE. More »»

Publication Type: Book

Year of Conference Publication Type Title

2012

Book

K. P. Soman and Dr. Ramanathan R., Digital Signal and Image Processing-The Sparse Way, 1stEditionst ed. Elsevier India, 2012, p. 480.[Abstract]


Digital Signal Processing Is Everywhere, It Is Pervasive And Ubiquitous. Its Methodologies Are Evolving And Spreading Its Wings Into Many Exciting New Directions Such As Networking, Bioinformatics, Digital Security And Forensics, And Spoken Language. As A Technology, It is a Phantom Technology Which Is Working From Behind The Scenes To Make Most Of Modern Day Devices Work. Designed For Both Undergraduate And Post Graduate Courses, This Book Provides A Comprehensive Insight Into The Linear Algebra And Optimization View Of Signal Processing That Can Be Readily Extended To Advanced Image Processing, Wavelet Theory And Compressive Sensing. This Book Shows How The Entire Class Of Problems In Signal And Image Processing Can Be Put In A Linear Algebra And Optimization Framework. More »»

Publication Type: Conference Proceedings

Year of Conference Publication Type Title

2010

Conference Proceedings

M. Chinnam, Madhusudhan, J., Nandhini, C., Prathyusha, S. N., Sw, S., and Dr. Ramanathan R., “Signal Detection in Software Defined Radar”, Second National Conference on Recent Trends in Communications, Computing and Signal Processing. Coimbatore, pp. 71 – 74 , 2010.

2009

Conference Proceedings

Dr. Ramanathan R. and , “Artificial Neural Network Approach to the Design of Band Pass Filters for Integrated Wireless Transceivers”, First National Conference on Recent Trends in Communications, Computing and Signal Processing. Coimbatore, pp. 53 – 56, 2009.

2009

Conference Proceedings

Dr. Ramanathan R. and , “Design and Analysis of Integrated Tunable Band Pass Filters for Phased Array Radar Receiver front ends”, National workshop on Design and Analysis of Radar Systems,DARS 2009. ISRO, Bangalore, 2009.

2008

Conference Proceedings

Dr. Jayakumar M., Dr. Ramanathan R., and B, S. Narayanan, “Air Substrate Based Shorted Rectangular Patch for Air Borne Vehicles”, International Conference on Aerospace Science and Technology (INCAST -2008). National Aerospace Laboratories, Bangalore, p. 139, 2008.

2008

Conference Proceedings

Dr. Ramanathan R. and , “Design and Analysis of Compact and Highly Selective Band Pass Filter for use in non invasive Bio Medical sensing using Ultra Wide Band Communications and Radar Technology”, National Symposium on Instrumentation (NSI 33). Instrument Society of India, Vishakhapatnam, 2008.

2008

Conference Proceedings

Dr. Ramanathan R. and , “Novel Technique for Designing a Planar Antenna for Broadband applications”, National Conference on VLSI, Embedded Systems, Signal Processing and Communication Technologies (NCESCOM 08). Chennai, 2008.

2008

Conference Proceedings

Dr. Ramanathan R. and , “Design Analysis of Printed Dual- Band Antenna for Wireless Application”, The Fourth National Conference on Recent Trends in Communication Techniques, NATCON -08. Nagercoil, 2008.

2008

Conference Proceedings

Dr. Ramanathan R. and , “Investigation of Reconfigurable Slot Antennas for WLAN Applications”, The National Conference on Broad Band Technologies (BROADBAND-08). Mar Baselios College of Engineering and Technology, Thiruvananthapuram, 2008.

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