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Ujjinimatad R.,Ballari Institute of Technology and Management
2013 Annual International Conference on Emerging Research Areas, AICERA 2013 and 2013 International Conference on Microelectronics, Communications and Renewable Energy, ICMiCR 2013 - Proceedings

In this paper, we consider the sensing methods based on the known noise level in cognitive radio (CR) networks under multi antenna systems and compare with the unknown noise level detection methods. The analysis is focused on energy detection (ED) and maximum eigenvalue based methods that require the knowledge of noise level. Threshold and detection performance of the maximum eigenvalue based method are expressed by closed analytical formulas. Random matrix theory is used to derive the expressions for threshold and probability of detection. The performance comparison of different sensing methods is provided through simulation analysis. Simulation results provide performance of various sensing methods for wireless microphone signals and independent and identically distributed (iid) signals. © 2013 IEEE. Source

Thomas H.M.W.,Ballari Institute of Technology and Management | Kumar S.C.P.,Rashtreeya Vidyalaya College of Engineering
Proceedings of the 2015 International Conference on Applied and Theoretical Computing and Communication Technology, iCATccT 2015

FPGA knowledge has become object for the realization of real time algorithms appropriate for image processing applications. MATLAB GUI allow designer to unlock the picture to be processed, setup the message parameters, identify the essential processing, drive the input picture, and obtain the related outcome after the method. This could be processed in real time. We can implement existing system for simplified computation method on a MRI image for tumor detection is detailed above using morphological filtering on a binary image which is extracted from the input image & also we can implement for the work carried out for the detection of desired interest based on morphological operation and segmentation algorithm is developed The algorithm is been tried on a amount of diverse images from various angles and the output results were almost desired. © 2015 IEEE. Source

Ujjinimatad R.,Ballari Institute of Technology and Management
IET Communications

In this study, the authors consider the problem of signal detection in cognitive radio under the cases of known and unknown noise levels. The analysis is focused on maximum eigenvalue-based method which requires the knowledge of noise variance and the ratio of maximum eigenvalue to the trace of covariance matrix. The analytical formulas are derived for threshold calculation and probability of detection for the considered methods. Performance of the considered methods is measured through simulation analysis. The performance comparison between the considered methods and other existing methods is provided. Simulations based on independent and identically distributed signals and wireless microphone signals are presented to verify the various sensing methods. © The Institution of Engineering and Technology 2013. Source

MacHappa T.,Ballari Institute of Technology and Management | Prasad M.,Gulbarga University
Bulletin of Materials Science

'In situ' polymerization of polyaniline (PANI) was carried out in the presence of magnesium chromate (MgCrO 4) to synthesize PANI/ceramic (MgCrO 4) composite. These prepared composites were characterized by XRD, FTIR and SEM, which confirm the presence of MgCrO 4 in polyaniline matrix. The temperature dependent conductivity measurement shows the thermally activated exponential behaviour of PANI /MgCrO 4 composites. The decrease in electrical resistance was observed when the polymer composites were exposed to the broad range of relative humidity (ranging between 20 and 95% RH). This decrease is due to increase in surface electrical conductivity resulting from moisture absorption and due to capillary condensation of water causing change in conductivity within the sensing materials. PANI / MgCrO 4 composites are found to be sensitive to low humidity ranging from 20 to 50% RH. © Indian Academy of Sciences. Source

Ujjinimatad R.,Ballari Institute of Technology and Management
2012 National Conference on Computing and Communication Systems, NCCCS 2012 - Proceeding

Cognitive Radio (CR) systems offer the opportunity to improve spectrum utilization by detecting unoccupied spectrum band and adapting the transmission to those bands while avoiding the interference to primary users. Spectrum sensing is the fundamental task in cognitive radio and it needs to detect signals presence under strict requirement such that secondary users (unlicensed users) can use the licensed spectral band without interfering primary users (licensed users). Energy Detection (ED) is a widely used spectrum sensing method for CR networks since it is very easy to implement and does not require any knowledge of the primary signal. However, ED requires accurate noise power to perform the detection and its performance is poor at low SNR and very sensitive to noise uncertainty. ED is optimal for detecting independent and identically distributed (iid) signals, but not optimal for detecting correlated signals. To overcome the limitations of ED, a novel approach is proposed based on the correlations of the sample covariance matrix computed from the random data matrix of the received signal samples in this paper. This approach does not need any information of the signal, the channel and noise power as a priori. Simulation approach is used to set the threshold for the target probability of false alarm. Since sample covariance matrix catches the correlations among the signal samples, the proposed method is better than the energy detection algorithm. Simulations based on recorded voice signals and iid signals are presented to verify the proposed method and results are compared with ED algorithm. © 2012 IEEE. Source

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