iosr-JECE   International Conference on Future Technology in Engineering – ICFTE'16

Abstract: This paper presents the design of a broadband rugged power amplifier (PA) operating from 50 to 500MHz, with an output power of more than 15W. The intended application is in the transmitter module of a manpack military radio. The implemented power amplifier exhibits a power gain of 17±1.5dB from 50 to 500MHz band with its power added efficiency (PAE) being greater than 35%, and the second and third-harmonic distortions are below -16dBc and -15dBc, respectively, at an output power of 15W over the entire frequency band. The design incorporates transmission line transformers for broadband impedance matching. A highly rugged Laterally-Diffused...........
Keywords - RF Power Amplifier, Rugged PA, Broadband PA, High VSWR, Transmission line transformer.

[1] Steve C. Cripps, "RF Power Amplifiers for Wireless Communications"
[2] Pradeep Rajagopal and Ray Crampton, "Nitronex targets military radios"
[3] Jerry Sevick, "A Simplified Analysis of the Broadband Transmission Line Transformer", February 2004 High
Frequency Electronics
[4] J. Cho et al., "Design of a 100watt high-efficiency power amplifier for the 10-500MHz band," 2009 Asia Pacific
Microwave Conference, Singapore, 2009, pp. 285-288.
[5] NXP Datasheet, "Document Number: MRFE6VS25LRev. 0, 10/2012"

Abstract: The primary aim of this paper is to get advantage of computer based system. The Hardware PID is replaced with soft PID that has equal controlling capabilities as that of instrument. Virtual Instrumentation PID controller is implemented using software called LabVIEW developed by National Instruments. We have used a Data Acquisition board (DAQ) for interfacing with the hardware. This DAQ card is product of the same company National Instruments.The process is a Multi-loop Trainer set up mounted with a tank whose level has to be controlled using a feedback control loop. The flow of project execution is: The measured inputs to the designed PID will be provided by Level transmitter............

Keywords – I/P coverter , LabVIEW, PID Controller, pressure transmitter

[1]. Comparison of PID Controller Tuning Methods Mohammad Shahrokhi and Alireza Zomorrodi Department of Chemical Petroleum Engineering Sharif University of Technology
[2]. PID CONTROLLER TUNING: IMPROVEMENT OF CLASSIC APPROACHES IN CHEMICAL PROCESSES Behnam Baloochy* Department of Modelling and Process Control, Technology Development Research Division, Research Institute of Petroleum Industry, Tehran, Iran,
[3]. Designing PID Controller using LabVIEW for Controlling Fluid Level of Vessel Harsh Kaji, Shruti Annigeri, Prof. Prafulla Patil / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 3, Issue 2, March -April 2013, pp.1329-1333 1329 | P a g e
[4]. LABVIEW BASED TUNING OF PI CONTROLLERS FOR A REAL TIME NON LINEAR PROCESS M.KALYAN CHAKRAVARTHI, NITHYA VENKATESAN VIT University, Vandalur-Kelambakkam road, Chennai, TamilNadu,600127.

Abstract: This paper proposes a novel design procedure of proportional- derivative (PD)-like fuzzy logic controller (FLC) for dc–dc converters. The design procedure allows the state space model of the converter and linear control design techniques to be used in the initial stages of FLC design. This simplifies the design and the stability assessment of the FLC. By exploiting the fuzzy logic structure of the controller, heuristic knowledge is incorporated in the design, which results in a nonlinear controller with improved performance over linear PD controllers.

Keywords: Boost converter, Fuzzy control, and Proportional–Derivative (PD) control.

[1] W. C. So, C. K. Tse, and Y. S. Lee, "Development of a fuzzy logic controller for DC–DC converters: Design, computer simulation, and experimental evaluation," IEEE Trans. Power Electron., vol. 11, no. 1, pp. 24–31, Jan. 1996.
[2] P.Mattavelli, L. Rossetto, G. Spiazzi, and P. Tenti, "General purpose fuzzy controller for DC–DC converters," IEEE Trans. Power Electron., vol. 12, no. 1, pp. 79–86, Jan. 1997.
[3] Y. Shi and P. C. Sen, "Application of variable structure fuzzy logic controller for DC–DC converters," in Proc. IECON, 2001, pp. 2026–2031.
[4] L. Guo, J. Y. Hung, and R.M. Nelms, "Experimental evaluation of a fuzzy controller using a parallel integrator structure for DC–DC converters," in Proc. ISIE, 2005, vol. 2, pp. 707–713.
[5] A. Gad and M. Farooq, "Application of fuzzy logic in engineering problems," in Proc. IECON, 2001, pp. 2044–2049.

Abstract: This paper discusses a novel technology which helps the paralysed people to communicate using their eyes. With the aid of this device, the user is able to control the entire computer using their eyes. It uses a modified PS3 eye camera and IR illuminators along with specified software's to track the position of user's pupil .It will also be locally maintainable. We introduce a technology that not only help them to communicate but also is cost effective.
Keywords- Communicate, Control, Eye camera, Illuminators, Pupil.

[1]. David A. Robinson: A method of measuring eye movement using a scleral search coil in a magnetic field, IEEE Transactions on Bio-Medical Electronics, October 1963, 137–145
[2]. The Eye: A Survey of Human Vision; Wikimedia Foundation
[3]. Sigut, J; Sidha, SA (February 2011). "Iris center corneal reflection method for gaze tracking using visible light.". IEEE transactions on bio-medical engineering. 58 (2): 411–9.
[4]. Majaranta, P., Aoki, H., Donegan, M., Hansen, D.W., Hansen, J.P., Hyrskykari, A., Räihä, K.J., Gaze Interaction and Applications of Eye Tracking: Advances in Assistive TechNielsen, Jakob. Pernice, Kara. (2010).
[5]. "Eyetracking Web Usability." New Rideres Publishing. p. 11. . Google Book Search. Retrieved on October 28, 2013.nologies, IGI Global, 2011

Abstract: Image compression is basically a process of encoding the image to trim down the size of image as a number of bytes for storage and transmission purposes, while maintaining as much as possible the quality of the image. The quality of the image of most importance in any compression technique with a good compression ratio. The compressed image requires less memory space and less transmission time. A number of techniques have been developed in image processing. This paper gives a detailed view of Lossy and Lossless compression techniques and also the architectures of most efficient transforms such as Discrete Wavelet Transform (DWT)...........

Keywords – Artificial Neural Networks (ANN), Artificial Neural Network and Fuzzy Inference System (ANFIS), Differential Pulse Code Modulation (DPCM), Discrete Wavelet Transform (DWT).

[1] Vilas H Gaidhane, Vijander Singh, Yogesh V Hote and Mahendra Kumar, New Approaches for Image Compression Using Neural Networks, Journal of Intelligent Learning Systems and Applications, 3, 2011, 220-229.

[2] SS Panda, MSRS Prasad, MNM Prasad and SKVR Naidu, Image Compression Using Back Propagation Neural Network, International Journal of Engineering Science and Advance Technology (IJESAT), ISSN: 2250 – 3676, Vol 2, Issue – I, Jan – Feb 2012, 74 – 78,.

[3] Birendra Kumar Patel and Prof. Suyash Agrawal, Image Compression Techniques Using Artificial Neural Network, International Journal of Advance Research in Computer Engineering and Technology (IJARCET) Vol-II, Issue-10, Oct 2013.

[4] Vinit D Raut and Surekha Dholay, Analysing Image Compression with Efficient Transforms and Multistage Vector Quantisation Using Radial Basis Function Neural Network, IEEE International Conference on Engineering and Technology (ICETECH), 20th March 2015, Coimbatore, Tamil Nadu.

Abstract: The main challenge faced during the implementation of Multiple Input Multiple Output(MIMO) Orthogonal Frequency Division Multiplexing (OFDM)System is that it is subjected to impairments of frequency and timing offsets which causes performance degradation of the system. Preamble based offset estimation techniques are equipped with mathematical sequences in the header of each OFDM frame. To ensure accurate estimation of offsets, selection of apt sequence is crucial. The sequences with high autocorrelation properties and low autocorrelation side lobes are preferred. A test bed for analyzing the correlation properties and side lobe level of the sequence is developed and discussed in this paper.
Keywords: MIMO OFDM, Timing Metric, Schmidl and Cox algorithm, Minn's Algorithm, Gold, Kasami, Barker, GCL.

[1]. T.M. Schmidl, D. Cox, "Robust frequency and timing synchronization in OFDM", IEEE Trans. on Comm., vol. 45,1997. pp. 1613-1621,
[2]. H. Minn, M. Zeng, and V. K. Bhargava, "On timing offset estimation for OFDM systems", IEEE Comm. Letters, vol. 4, no. 7, 2000, pp. 242-244.
[3]. Van de Beek, J. J., Sandell, M., & Borjesson, P. O., "ML estimation of time and frequency offset in OFDM systems", IEEE Trans. Signal Proceedings. 45, 1997, pp. 1800–1805.
[4]. P.H. Moose, "A Technique for Orthogonal Frequency Division Multiplexing Frequency Offset Correction", IEEE Trans. on Communications, vol. 42, no. 10,1994, pp. 2908-2914.
[5]. A.N. Mody and G.L. Stuber, "Synchronization for MIMO OFDMSystems", IEEE Global Communications Conference 2001, vol. 1, 2001, pp. 509-513.

Abstract: One of the emerging areas in the field of next generation wireless network is the Cognitive Radio Network (CRN). The traditional spectrum access approach leads to vast underutilization of the radio spectrum assigned to primary (licensed) users. The dynamic spectrum access is the most suitable approach to achieve finest spectrum utilization. The dynamic spectrum access technique allows the secondary (unlicensed) users to sense and use the available spectrum opportunistically, hence also known as opportunistic spectrum access. In this paper, an approach using a Sugeno type Fuzzy Logic System (FLS) to control the spectrum access has been proposed.............

Keywords - Cognitive radio network, Fuzzy logic system, Soft computing

[1]. Hong-Sam T. Le and Hung D. Ly, "Opportunistic Spectrum Access Using Fuzzy Logic for Cognitive Radio Networks", In. Proc. Secondinternational conference on electronics, pp 240-245, 2008.
[2]. Spectrum Policy Task Force report, Technical report 02-135, Federal communications commission, Nov. 2002.
[3]. Simon Haykin, "Cognitive radio: Brain-empowered wireless communication", IEEE Journal on Selected Areas in Communications, vol. 23, no. 5, Feb 2005, pp. 201-220.
[4]. R. Tandra and A. Sahai, "Fundamental limits on detection in low SNR under noise uncertainty", International Conference on Wireless Networks,Communications and Mobile Computing, vol. 1, Jun. 2005, pp.464-469.
[5]. Ben Wild and KannanRamchandran, "Detecting primary receivers for cognitive radio applications", IEEE Proc. on DySPAN 2005,, Nov. 2005, pp.124-130.