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Bangalore, India

Kalaiarasi M.,Sir MVIT | Vigneswaran T.,Vellore Institute of Technology
Journal of Theoretical and Applied Information Technology | Year: 2016

Compression technique is significant in day to day scenario for smooth transmission of data. By utilizing this technique the bandwidth utilization is reduced. Even compression techniques help us for efficient memory utilization to make overall data transmission better. Data size in different cases is quite huge and difficult to send without compressing it. In the bio- medical arena, it is applicable because of the large image size, but at the same time it is having its own challenges in terms of data loss. While reconstructing the image, the possibility of data loss or quality loss comes into picture. Though there are many techniques which suggest lossless compression and decompression but still refinement is required. There are techniques using discrete wavelet transform to do the lossless image compression. The recent one is the Three-Dimensional Discrete Wavelet Transform (3-D DWT). In this research work, a lifting based Discrete Wavelet Transform architecture for three dimensional images is presented. The proposed architecture has been implemented on Xilinx Virtex-6 Series Field-Programmable Gate Array (FPGA). Implementation results show the efficiency of proposed system in terms of power consumption and operating frequency. The proposed architecture of Discrete Wavelet Transform achieves a maximum operating frequency of 298 MHz with a power consumption of 7 mW. © 2005 - 2016 JATIT & LLS. All rights reserved. Source


Rajesh N.,Sir MVIT | Rajesh N.,Tamil University | Selvakumar A.A.L.,Rajiv Gandhi Institute of Technology
International Journal of Advanced Intelligence Paradigms | Year: 2015

Privacy preserving data mining (PPDM) is a new direction in the area of data mining, where privacy preserving techniques have been applied to maintain the data privacy. Example through the process of data mining the sensitive data of an individual can be inferred as well as personal information and patterns from non-sensitive data. PPDM (Rajesh and Selvakumar, 2014) based on enumeration and concatenation of attributes using k-anonymity where, the original data is combined using only two attributes to show encrypted one quasi-identifier. So, we proposed a new approach called hiding personalised anonymity for enumerating and concatenating of attributes using PPDM for combination of three attributes to show encrypted one quasi-identifier. We can reconstruct the attributes using encrypted attribute. In this work, we proposed PPDM for combination of three attributes and two level encrypting methods in order to protect the more secure personal information for avoiding sensitive issues using unlimited records. © 2015 Inderscience Enterprises Ltd. Source


Anitha M.,Sir MVIT | Kurahatti N.G.,EPCET
2015 IEEE Underwater Technology, UT 2015 | Year: 2015

In Multi-sensor data fusion technology, array processing is an area of signal processing. A sensor array captures spatially propagating signals arriving from a certain direction and processes them to obtain useful information. To this end, it is intended to linearly combine the signals from all the sensors with coefficients in a manner, so as to estimate transmitted data radiating from a specific direction. In beamforming, an array processor steers a beam to a certain direction by computing a properly weighted sum of the individual sensor signals just as an finite impulse response (FIR) filter generates an output (at a frequency of interest) that is the weighted sum of time samples. Current methods to calculate the weight coefficients are complex. Designed model is a simple and effective weight coefficient calculation method based on improved decision tree model where it combines the best features of neural network and decision trees. This technique is based on the optimum beamformer and makes it robust to an faulty estimate of the Direction Of Arrival (DOA) even when powerful interferences are within the uncertainty range of the desired source. The proposed algorithm is the product of an effort to provide more efficient procedure for real time implementation of array signal processing and is useful for wireless communication with Binary Phase Shift Keying signalling. © 2015 IEEE. Source


Anitha M.,Sir MVIT | Kurahatti N.G.,EPCET
2015 International Conference on Communication and Signal Processing, ICCSP 2015 | Year: 2015

In the information technology age, multisource multi-sensor information fusion encompasses the theory, methods and tools conceived and used for exploiting synergy in the information acquired from multiple sources databases, sensors. In Multi-sensor data fusion technology, array processing is an area of signal processing that has powerful tools for extracting information from signals collected using an array of sensors. A sensor array captures spatially propagating signals arriving from a certain direction and processes them to obtain useful information. To this end, we intend to linearly combine the signals from all the sensors with coefficients in a manner, so as to estimate transmitted data radiating from a particular direction. Current methods to calculate the weight coefficients are complex. simple and effective weight coefficient calculation method is considered and which is based on where the best features of neural network and fuzzy logic is combined. This technique is based on the optimum beamformer and makes it robust to an faulty estimate of the Direction Of Arrival (DOA) even when powerful interferences are within the uncertainty range of the desired source or contact. The new modified beamformer algorithm is the product of an effort to provide more efficient procedure for real time implementation and a better estimate of the position and spectrum of the contact which is helpful in measurement data fusion or localization. © 2015 IEEE. Source


Sowmya R.,Sir MVIT | Murthy C.R.,IISC
Proceedings of 16th National Conference on Communications, NCC 2010 | Year: 2010

This paper considers the design and analysis of a filter at the receiver of a source coding system to mitigate the excess distortion caused due to channel errors. The index output by the source encoder is sent over a fading discrete binary symmetric channel and the possibly incorrect received index is mapped to the corresponding codeword by a Vector Quantization (VQ) decoder at the receiver. The output of the VQ decoder is then processed by a receive filter to obtain an estimate of the source instantiation. The distortion performance is analyzed for weighted mean square error (WMSE) and the optimum receive filter that minimizes the expected distortion is derived for two different cases of fading. It is shown that the performance of the system with the receive filter is strictly better than that of a conventional VQ and the difference becomes more significant as the number of bits transmitted increases. Theoretical expressions for an upper and lower bound on the WMSE performance of the system with the receive filter and a Rayleigh flat fading channel are derived. The design of a receive filter in the presence of channel mismatch is also studied and it is shown that a minimax solution is the one obtained by designing the receive filter for the worst possible channel. Simulation results are presented to validate the theoretical expressions and illustrate the benefits of receive filtering. ©2010 IEEE. Source

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