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i-manager's Journal on Communication Engineering and Systems (JCS)

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Design and Development of Patient Care Voice Actuated Bed in Hospital
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A Miniaturized Dual L Shaped with Truncated Ground Rectangular Monopole Antenna for 5G and Wireless Communications
A Centre C-Shaped Dual Band Rectangular Monopole Antenna for Wi-Fi and Wireless Communication
Impact of Subchannel Symbol Rates on WSS Filtering Penalty in Elastic Optical Networks: A Comparative Study

Most Cited

Volume 1 Issue 2 February - April 2012

Research Paper

Analysis Of Atmospheric Radar Echoes Using Fft And Matched Filter For Doppler Profile Detection

PADMAJA* , S. Varadarajan**

* Research Scholar, S.V.U College of Engineering, Tirupati

** Professor of ECE, S.V.U College of Engineering, Tirupati

Padmaja, N. and Varadarajan, S. (2012). Analysis Of Atmospheric Radar Echoes Using FFT And Matched Filter For Doppler Profile Detection. i-manager’s Journal on Communication Engineering and Systems, 1(2), 1-5. https://doi.org/10.26634/jcs.1.2.1769

Abstract

A new algorithm for Doppler profile detection of Radar echoes using Matched Filter is developed in this paper. The algorithm is applied to the time series radar data obtained from the mesosphere- stratosphere- troposphere (MST) region near Gadanki, Tirupati Matched filter is often referred to as optimum filter. The most unique characteristic of the matched filter is that it produces the maximum achievable instantaneous SNR at its output when a signal plus additive white noise is present at the input. This presents a new technique adopted when information regarding all the range bins is available and the processing load can be handled. The results are compared with the traditional FFT technique and are presented for the performance evaluation. The merits and limitations of this method of detecting dopplers in comparison to FFT are discussed.

References

[1]. Bassem R. Mahafza (2000). “Radar System Analysis using Matlab,” 2nd edition, Chapman and Hall /CRC.

[2]. Doviak, R.J., and Zrnic, D.S. (1984). “Doppler Radar and Weather Observations”, 2nd Edition, Academic Press.

[3]. Giannakis, G.B., and Tsatsanis, M.K. (1990). “Signal Detection and classification using Matched Filtering and Higher order statistics”, IEEE Transactions on Accoustic Speech Signal Processing, Vol. 38, pp 284-296.

[4]. Rottger, J. (1984). “The MST radar technique in Hand Book for MAP,” edited by R.A. Vincent. Vol. 3, pp 187-232.

[5]. Skolinik, M.I. (1980). “Introduction to Radar systems”, 2nd ed., McGraw-Hill, New York.

[6]. Gold, B., and Rader, C. (1969). “Digital Processing of Signals”, Lincoln Laboratory Journal, pp. 297-320, McGraw- Hill, New York.

[7]. Proakis John, G., and Dimitris G. Manolakis, (1996). “Digital signal processing,” 3rd Ed., Printice Hall.

[8]. Gabor, D. (1946). “Theory of Communication”, Journal of Institute for Electrical Engineers, Vol.93, pp. 429-439.

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Research Paper

ROI Segmentation On DICOM Image In Presence Of Noise Based On Morphology

T. Surendra Nath* , V. Kalpana, Vijaya Kishore*

* PG Student, Communication Systems, SITAMS, Chittoor

PG Student, Communication Systems, SITAMS, Chittoor

* Professor, Department of ECE, SITAMS, Chittoor

Nath, T. S., Kalpana, V., and Kishore, V. V. (2012). ROI Segmentation On DICOM Image In Presence Of Noise Based On Morphology. i-manager’s Journal on Communication Engineering and Systems, 1(2), 6-11. https://doi.org/10.26634/jcs.1.2.1770

Abstract

Various medical imaging available are MRI, CT, US and DICOM. Automated Computer Aided Diagnosing (CAD) system detects lung cancer with improved diagnostic radiology. Several approaches to lung CAD combine geometric and intensity models to enhance local anatomical structure. Two difficulties those are primarily associated with the detection of nodules include the detection of nodules that are adjacent to vessels or the chest wall when they have very similar intensity; and the detection of nodules that are non-spherical in shape. In such cases, intensity thresholding or model based methods might fail to identify those nodules. In this paper Region of interest segmentation of DICOM lung image is performed in the noisy environment such as Poisson and speckle using morphology and watershed algorithm. The ROI lung area blood vessels and nodules from the major lung portion are extracted achieved using different edge detection operators such as Sobel, Prewitt and LoG in presence of noise. The results are helpful to study and analyse the influence of noises on the DICOM images in extracting region of interest.

References

[1]. H. Chidiac, & D. Ziou, (1999). “Classification of image Edges”, Vision interface'99, Troise-Rivieres, Canada, pp. 17- 24.

[2]. Zhao Yu qian., & Gui Wei-hua (2005). ”Medical Images edge detection Based on Mathematical Morphology”, Proceedings of 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[3]. Speeuwers, L.j., Heijden, F. Van der, (1992). “Evaluation of Edge Detectors using Average Risk”,Robust Computer Vision (Eds : Forstner/ Ruwiedel), Wichmann, Karlsruhe:

[4]. M. Heath, S. Sarker, T. Sanocki and K. Bowyer (1996). “Comparison of Edge Detectors: A Methodology and Initial Study”, Proceedings of CVPR'96 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 143-148.

[5]. Tuba Sirin, Mehmet Izzet Saglam et al. “A Comparative Evaluation of Competitive Learning Algorithms for Edge detection Enhancement”,

[6]. Shin, M.C., Goldgof, D.B., Bowyer, K.W., & Nikiforou, S. (2001). ”Comparision of edge detection algorithms using structure from motion task” Systems, Man and Cybernetics, Part B, IEEE Transactions, Vol. 31,Issue 4, pp.589-601.

[7]. Mohsen Sharifi, Mahmoud Fathy, (2002). “A Classified and Comparitive Study of Edge detection Algorithms”, Proceedings of International Conference on Information Technology: Coding and Computing (ITCC'02) IEEE

[8]. RamanMaini and J.S. Sohal, (2006). ”Performance Evaluation of Prewitt Edge Detector for Noisy Images”, GVIP Journal, Vol. 6, Issue 3, Dec.

[9]. Mohamed Roushdy, (2006). ”Comparitive Study of Edge detection Algorithms Applying on the Gray Sacle Noisy Image using Morphological Filter”, GVIP Journal, Vol. 6,Issue 4,Dec.

[10]. E. Clavier, S. Clavier, & J. Labiche, (1999). “Image Sorting-Image Classification: A Global Approach”, icdar'99, Proceedings of the Fifth International IEEE Conference on Document Analysis and Recognition, pp. 123-126.

[11]. R.M. Haralick, & L.G. Slhapiro, (1992). “Computer and Robot Vision”, Vision 1, Addition- Wesley Publishing Company Inc.

[12]. Albovik, (2000). ”Handbook of Image and video Processing”, Academic Press,

[13]. P. Garcia, F. Pla, & I. Garcia, (1999). “Detecting Edges in color Images using dichromatic Differences”, Seventh International IEEE Conference on Image processing and ITS Applications, volume: 1, pp.363-367.

[14] K. Timmermann and R. Novak (1999). ”Multiscale modelling and estimation of Poisson processes with applications to photon-limited imaging”, IEEE, Trans Information Theory, Vol. 45,No.3, pp.846-852.

[15]. S.G. Chang, Y. Binand, & M. Vetterli: (2006). ”Adaptive wavelet thresholding for image denoising and compression”, IEEE Trans. on Image Processing, vol.9 no.9, pp. 1532-1546,sep.

[16]. L. Gagnon and F.D. Smaili: (1996). ”Speckle Noise Reduction of Airborne SAR Images with Symmetric Daubechies Wavlets”, SPIE Proc. #2759, pp. 1424.

[17]. Z. Wang and D. Hang, (1999). ” Progressive Switching Median Filter for the Removal of Impulse Noise from Highly Corrupted Images”, IEEE Trans. on Circuits and Systems –II:Anlog and Digital Signal Processing, Vol. 46, No. 1, pp.78-80, Jan.

[18]. H.E Durdick (1977). Digital imaging: theory and applications, Mcgraw-Hill,

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Research Paper

Curvelets with New Quantizer for Image Compression

G. Jagadeeswar Reddy* , T. Jaya Chandra Prasad, M. N. Giri Prasad, M. Madhavi Latha, T. Satya Savithri

ECE Department, EVMCET, AP, India

ECE Department, RGMCET, Kurnool, AP, India.

ECE Department, JNTUCE, Pulivendula, AP, India.

ECE Department, JNTUH, Hyderabad, A.P, India.

ECE Department, JNTUH, Hyderabad, A.P, India.

Reddy, G. J., Jayachandraprasad, T., Giriprasad, M. N., Latha, M. M., and Savithri, T. S. (2012). Curvelets With New Quantizer For Image Compression. i-manager’s Journal on Communication Engineering and Systems, 1(2), 12-16. https://doi.org/10.26634/jcs.1.2.1771

Abstract

This paper emphasizes on designing of a novice quantizer that is more suitable for compressing images through new transform known as curvelet transform. The new transform is believed to capture image information more efficiently than the wavelet transform by providing basis elements in addition to possessing the qualities of wavelet. It was designed to represent edges and other singularities along curves much more efficiently than traditional transforms, i.e. using many fewer coefficients for a given accuracy of reconstruction. This compression algorithm is tested on various images like plain, textured and building images. The results are compared with the existing techniques like curvelet with existing quatizer, wavelet with existing quantizer and wavelet with proposed quantzer. The proposed algorithm “curvelets with proposed quantizer” outperforms the existing techniques. The performance is evaluated through visual clarity, Peak Signal to Noise Ratio (PSNR) and compression metrics such as Compression ratio and Bit-rate.

References

[1]. F.G. Meyer and R.R. Coifman (1997 ). “Brushlets: a tool for directional image analysis and image compression,” Applied and Computational Harmonic Analysis, pp.147- 187.

[2]. Colm Mulcahy, “Image compression using the Haar wavelet transform” Spelman Science and Math journal, pp:22-31.

[3]. J. Rissanen, “Stochastic Complexity in Statistical Inquiry,” World Scientific, 189.

[4]. G.J. Sullivan (1996 ). “Efficient Scalar Quantization of Exponential and Laplacian Random Variables,” IEEE Trans. on Information Theory,Vol. 42, No.5, pp.1365-1374; Sept .

[5]. M.N. Do, and M. Vetterli (2000). “Orthonormal finite ridgelet transform for image compression,” in proc. IEEE Int. Conf. Image Processing (ICIP), Sept.

[6]. Pat Yip, (2000). “The Transform and Data Compression Handbook”, CRC Press ; sept.

[7]. M.L. Hilton, (1994). “Compressing still and Moving Images with wavelets”, Multimedia systems, Vol.2, No.3.

[8]. Anil K. Jain, (2000). “Fundamentals of Digital Image Processing”, Prentice Hall.

[9]. E.J. Candes and D.L. Donoho, (1999). “Curvelets.” Manuscript. http://www.stat.stanford.edu/~donoho/ Reports/1998/curvelets.zip; 1999.

[10]. Candes, E., Demanet, L., Donoho, D., and Ying, L. (2005). “Fast Discrete Curvelet Transforms,” Applied and Comp. Math., Caltech; July.

[11]. M. Frazier, B. Jawerth, and G. Weiss, (1991). “Littlewood- Paley Theory and the study of function spaces”. NSF-CBMS Regional Conf. Ser in Mathematics, 79. American Math. Soc.: Providence, RI; 1991.

[12]. D. Marr and E. Hildreth, (1980). “Theory of edge detection," Proc. Royal Society of London B 207, pp. 187- 217.

[13]. S.G. Mallat, (1989). “A theory for multiresolution signal decomposition: the wavelet representation," IEEE Transactions on Pattern Analysis and Machine Intelligence 11(7), pp. 674-693.

[14]. E. Simoncelli, W. Freeman, E. Adelson, and D. Heeger, “Shiftable multi-scale transforms [or "what's wrong with orthonormal wavelets"]," IEEE Trans. Information Theory ;1992.

[15]. B. Alpert, G. Beylkin, R. Coifman, and V. Rokhlin, (1993). “Wavelet-like bases for the fast solution of secondkind integral equations," SIAM J. Sci. Comput.

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Research Paper

Performance Analysis Of CDMA System Using Power Control Algorithm With AWGN Channel

G. Brindha*

Assistant Professor, Lord Jegannath College of Engineering and Technology

G. Brindha (2012). Performance Analysis Of Cdma System Using Power Control Algorithm With Awgn Channel. i-manager’s Journal on Communication Engineering and Systems, 1(2), 17-22. https://doi.org/10.26634/jcs.1.2.1772

Abstract

Continuation of an active call is one of the most important quality measures in cellular communication systems. Handoff process in the cellular system enables to provide such facility by transferring an active call from one cell to another cell.Signals transmitted over a multipath propagation channel can exhibits inter path interference and fading. To overcome the multipath effect, Rake receiver is used in CDMA technology. An important characteristic of a multipath channel is the time delay spread it causes to the received signal. This delay spread equals the time delay between the arrival of the first received signal component (LOS or multipath) and the last received signal component associated with a single transmitted pulse. Another characteristic of the multipath channel is its time-varying nature.Rake receiver is realized between the main path component and the local recovery carrier. In this paper the downlink performance parameters are estimated for a CDMA mobile system at the vertex of multiple adjacent cells. At the base station the received signal is coherently dispread and demodulated using a rake receiver. The effects of power control, error correction and rake receiver were also investigated and simulated based on the assumption that the received signals undergo Rayleigh fading.

References

[1]. ChingYao Huang, ChiehYuan Ho and HsuanLi Lin, (2008). Handoff Management in Cellular Systems. Recent Patents on Electrical Engineering 2008, 1, 225-230.

[2]. Nasif Ekiz, Tara Salih, Sibel Küçüköner, and Kemal Fidanboylu, (2005). An Overview of Handoff Techniques in Cellular Networks. Proceedings of World Academy Of Science, Engineering and Technology, Volume 6 June 2005, ISSN 1307-6884.

[3]. Hai Jiang and Curt H. Davis, (2005). "Coverage Expansion and Capacity Improvement from Soft Handoff for CDMA Cellular Systems”. IEEE Transactions on Wireless Communications, Vol. 4, No. 5, September.

[4]. Spatial Path separation and path diversity in 3G Multimedia Mobile Communication Using Intelligent Pre- Rake Processing in MISO channels, IEEE National Radio Science Conference, 2008.

[5]. Y. Hara, K. Suzuki, K. Kaneko, and T. Sekiguchi, (2005). Radio Resource Management and Power control for WCDMA uplink with high data rate packet transmission, IEICE.

[6]. Boris D. Andreev, Edward L. Titlebaum and Eby G. Friedman, (2004). Low power flexible rake receivers for WCDMA, ISCAS.

[7]. Abdurazak Mudesir, Power control algorithm in CDMA systems, International University Bremen.

[8]. Louis C. Yun and David G. Messerschmitt, Power Control for Variable QOS on a CDMA Channel, Department of Electrical Engineering and Computer Sciences University of California at Berkeley.

[9]. Matti Rintamäki Adaptive Power Control in CDMA Cellular Communication Systems, Helsinki University of Technology, Signal Processing Laboratory Teknillinen korkeakoulu.

[10]. I.B. Milstein, T.S. Rappaport, and R. Barghouti, (1992). “Performance evaluation for cellular CDMA,” IEEE Journal on Selected Areas in Communications, Vol. 10, No. 4, pp. 680–689.

[11]. A.N. Rosenberg and S. Kemp, (2003). “CDMA capacity and quality optimization”, McGraw-Hill.

[12]. Soumya Das, Sachin Ganu, Natalia Rivera, & Ritabrata Roy, Performance Analysis of Downlink Power Control in CDMA Systems email: fsoumya, sachin, nrivera, ritog@winlab.rutgers.ed.

[13]. Y. Hara, K. Suzuki, K. Kaneko, and T. Sekiguchi, (2005). Radio Resource Management and Power Control for WCDMA Uplink with High Data Rate Packet Transmission, IEICE Transactions on Communications, E88-B (5), pp. 2102–2109.

[14]. K.W. Sowerby and A.G. Williamson, (1988). “Outage probability calculations for a mobile radio systems with multiple interferers”, Electronic Letters, Vol. 24, No. 24, pp. 1511– 1513.

[15]. D.J. Torrieri, (1984). “The information bit-error-rate for block codes,” Transactions of Communications, Vol. COM- 32, pp. 474–476.

[16]. BER Comparison of Rayleigh Fading, Rician Fading and AWGN Channel using Chaotic Communication based MIMO-OFDM System Suchita Varade, Kishore Kulat.

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Research Paper

Analysis of Planar Tapered Dielectric Optical Waveguides using Matrix Approach without Considering the Reflection of the Fields at the Taper Boundary

S. K. Raghuwanshi*

Department of Electronics Engineering

Indian School of Mines Dhanbad, India.

Raghuwanshi, S. K., and Kumar, S. (2012). Analysis of Planar Tapered Dielectric Optical Waveguides Using Matrix Approach Without Considering The Reflection Of The Fields At The Taper Boundary. i-manager’s Journal on Communication Engineering and Systems, 1(2), 23-26. https://doi.org/10.26634/jcs.1.2.1773

Abstract

Optical waveguides are the building blocks of photonics circuits. They are used as, couplers, switches, splitters, multiplexer and de-multiplexer for optical signals. During the last two decades extensive study on analytical/numerical method in the field of optical waveguide has been done by different researchers. In this paper the matrix method has been applied to analyze taper waveguide (or bend waveguide) while considering the normal incidence of light and assumed to be no reflection from the first medium, where the light is being launched. The waveguide is assumed to be taper (bend). This type of waveguide structure is used in WDM optical communication system as a power splitter device.

References

[1]. Ajoy Ghatak and K. Thyagarajan, (2007).Optical Electronics, Cambridge University Press.

[2]. R. Scarmozzino, A. Gopinath, R. Pregla, and S. Helfert, (2000).Numerical Techniques for Modeling Guided-Wave Photonic Devices, IEEE J. Quantum Electron. 6 (2000) 150- 162.

[3]. W.P. Huang and C.L. Xu (1993). Simulation of Three- Dimensional Optical Waveguide by a Full-Vector Beam Propagation Method, IEEE J. Select. Quantum Electron. 29 (1993) 2639-2649.

[4]. C.L. Xu, W.P. Huang, S.K. Chaudhuri, and J. Chrostowski, (1994). An Unconditionally Stable Vectorial Beam Propagation Method for 3-D Structures, IEEE Photon. Technol. Lett. 6, 549-551.

[5]. J. Yamauchi, T. Ando, and H. Nakano, (1991). Beam Propagation Analysis of Optical Fibers by Alternating Direction Implicit Method, Electron. Lett. 27, 1663- 1665.

[6]. G.R. Hadley, (1992). Transparent Boundary Condition for the Beam Propagation Method, IEEE J. Quantum Electron. 28, 363-370.

[7]. K. Kawano and T. Kitoh, (2001). Introduction to Optical Waveguide Analysis, John Wiley & Sons, Inc.

[8]. S.K. Raghuwanshi and S. Talabattula, (2008). “Asymmetric pulse distortion due to pulse walk-off phenomena in wide-band DWDM Raman amplification systems", International J. of Engg. Research and Industrial Appls. (IJERIA), 1 (3), 209-223.

[9]. P. Jain, S.K. Raghuwanshi and S. Talabattula, (2005). “A novel approach to analyze Z-varying integrated optical waveguides", Proceedings of International conference on Optics & Optoelectronics, IRDE, Dehradun, India (PP-FIO- 22) 12-15 Dec.

[10]. S.K. Raghuwanshi, S. Talabattula and A. Selvarajan, (2006). “Fourier decomposition of the transverse field for analyzing optical waveguides using Beam Propagation method", J. Indian Inst. Sci., 86 (6), Nov.-Dec. 2006, 667- 680.

[11]. S.K. Raghuwanshi, Contemporary Optical Fiber Technology, Agarwal Publication, Agra, India 2011 (First Edition).

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Research Paper

Comparative Study of Different Medical Images with Noise Based On Morphology

V. Kalpana* , T. Surendra Nath, Vijaya Kishore*

* PG Student, Communication Systems, SITAMS, Chittoor.

PG Student, Communication Systems, SITAMS, Chittoor.

* Professor, Department of ECE, SITAMS, Chittoor.

Kalpana, V., Nath, T. S., and Kishore, V. V. (2012). Comparative Study Of Different Medical Images With Noise Based On Morphology. i-manager’s Journal on Communication Engineering and Systems, 1(2), 27-35. https://doi.org/10.26634/jcs.1.2.1774

Abstract

Medical images are diagnosed and demonstrated with their regional structures. Edge detection is a fundamental element in the field of image processing and computer vision for the extraction of features. Edge detection identifies and captures sharp intensity changes in an image. Medical image edge detection focus on object recognition of human organs. To detect the severity of disease several medical approaches like CT, MRI, PET, US and DICOM can be used. In this paper performance of CT and DICOM images using morphology and edge detection algorithms are evaluated in noisy environment. A comparision of different edge detecting algorithms by using several noises is performed and evaluated based on correlation coefficient and PSNR. The outcomes evaluate the resistivity of operators in presence of noise.

References

[1]. H. Chidiac, & D. Ziou, (1999). “Classification of image Edges”, Vision interface'99, Troise-Rivieres, Canada, 1999.pp. 17-24.

[2]. Zhao Yu qian, & Gui Wei-hua, (2005). ”Medical Images edge detection Based on Mathematical Morphology” Proceedings of 2005 IEEE Engineering in Medicine and Biology 27^th Annual Conference, Sep., 2005.

[3]. Speeuwers, L.j., & Heijden, F. Vander, (1992). “Evaluation of Edge Detectors using Average Risk”, Robust Computer Vision (Eds: Forstner/ Ruwiedel), Wichmann, Karlsruhe: 1992.

[4]. M. Heath, S. Sarker, T. Sanocki and K. Bowyer, “Comparison of Edge Detectors: A Methodology and Initial Study”, Proceedings of CVPR'96 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1996, pp. 143-148.

[5]. Tuba Sirin, Mehmet Izzet Saglam et al. “A Comparative Evaluation of Competitive Learning Algorithms for Edge detection Enhancement”.

[7]. Mohsen Sharifi, & Mahmoud Fathy, (2002). “A Classified and Comparative Study of Edge detection Algorithms”, Proceedings of International Conference on Information Technology: Coding and Computing (ITCC'02) IEEE 2002.

[8]. Raman Maini and J.S. Sohal, (2006). ”Performance Evaluation of Prewitt Edge Detector for Noisy Images”, GVIP Journal, Vol. 6, Issue-3, Dec.

[9]. Mohamed Roushdy,(2006) ”Comparative Study of Edge detection Algorithms Applying on the Gray Scale Noisy Image using Morphological Filter”, GVIP Journal, Vol- 6,Issue-4, Dec.

[11]. R.M. Haralick, & L.G. Slhapiro, (1992). “Computer and Robot Vision”, Vision 1, Addition- Wesley Publishing Company Inc.

[12]. Albovik, (2000). ”Handbook of Image and video Processing”, Academic Press.

[14]. K. Timmermann and R. Novak, (1999). ”Multiscale modelling and estimation of Poisson processes with applications to photon-limited imaging”, IEEE, Trans. Information Theory, Vol.45, no.3, pp.846-852.

[15]. S.G. Chang, Y. Binand, & Vetterli, (2006). ”Adaptive wavelet thresholding for image denoising and compression”, IEEE Trans. on Image Processing, Vol.9, No.9, pp. 1532-1546, Sep.

[16]. L. Gagnon and F.D. Smaili, (1996). ”Speckle Noise Reduction of Airborne SAR Images with Symmetric Daubechies Wavelets”, PIE Proc. #2759,pp. 1424.

[17]. Z. Wang and D. Hang, (1999). ” Progressive Switching Median Filter for the Removal of Impulse Noise from Highly Corrupted Images”, IEEE Trans. on Circuits and Systems II: Analog and Digital Signal Processing, Vol. 46.No. 1, pp.78- 80 Jan.

[18]. H. E Durdick, (1977). Digital imaging: theory and applications, McGraw-Hill, 1977.

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Review Paper

Evolutionary Approach of Adiabatic Logic Design on Low Power Solution –A Robust Survey

A. Kishore Kumar* , D. Somasundareswari, V.Duraisamy*****

* Dean, Electrical Sciences, Adithya Institute of Technology, Coimbatore, India.

* Professor & Principal, Hindustan College of Engineering & Technology, Coimbatore, India.

** Assistant Professor, ECE Department, Coimbatore Institute of Technology, Coimbatore, India.

Kumar, A. K., Somasundareswari, D., Duraisamy, V. and Pradeepa, T. S. (2012). Evolutionary Approach Of Adiabatic Logic Design On Low Power Solution - A Robust Survey. i-manager’s Journal on Communication Engineering and Systems, 1(2), 36-49. https://doi.org/10.26634/jcs.1.2.1775

Abstract

Adiabatic Logic styles in low power VLSI design have been examined for many years to achieve predictable low power design success. In this paper, we present a comprehensive literature review pertaining to the state-of-the-art issues in adiabatic logic designs and also focus on primary developments in this field that have taken place in the low power design. Various research papers and application notes have been referred to, for clear understanding of adiabatic logic designs on low power solutions. Major focus of this paper is to identify the gaps of the adiabatic logic designs and to narrow down the problems and requirements for its practical usage in semiconductor industries. Enough designs and methods have been proposed over last few decades, but the implementation of this logic, triggers the designer in various open points, which restricts further stems. This paper highlights the major open points and gives the solution for further design requirement to implement the adiabatic logic in semiconductor industries.

References

[1]. Cheryl Ajluni, (2009). “Existing Circuit Styles Shed Light on Low-Power Design”, Low Power Engineering Community (www.chipdesignmag.com).

[2]. J.G. Koller and W.C. Athas, (1992). “Adiabatic Switching, Low Energy Computing, and the Physics of Storing and Erasing Information”, Proceedings of the 2nd Workshop on Physics and Computation (PhysComp'92), pp. 267-270.

[3]. Gary K. Yeap, (1998). “Practical low power digital VLSI design” Springer.

[4]. A. Kishore Kumar, D. Somasundareswari, V. Duraisamy and M. Pradeepkumar (2010). “Low Power Multiplier Design Using Complementary Pass-Transistor synchronous Adiabatic Logic” International Journal on Computer Science and Engineering, Vol. 02, No. 07, 2291-2297.

[5]. Peiyi Zhao Zhongfeng Wang, (2009). “Low power design of vlsi circuits and systems”, IEEE 8th International Conference on ASIC, pages 17 – 20.

[6]. Michael A. Fury, (2012). “Reports on SEMI's Industry Strategy Symposium (ISS) 2012”, (www.electroiq.com)

[7]. R.T. Hinman and M.F. Schlecht, (1993). “Recovered Energy Logic – A Highly Efficient Alternative to Today's Logic Circuits”, Record of the 24th Annual IEEE Power Electronics Specialists Conference (PESC'93), pp. 17-26.

[8]. Younis, Saed G., and T.F. Knight Jnr (1994). “Asymptotically Zero Energy Computing Using Split-Level Charge Recovery Logic”, International Workshop on Low Power Design, pages 177-182.

[9]. A. Kramer, J.S. Denker, S.C. Avery, A.G. Dickinson and T. R. Wik, (1994). “Adiabatic Computing with the 2n-2n2d Logic Family”, Symposium on VLSI Circuits – Digest of Technical Papers, pp. 25-26.

[10]. A.G. Dickinson and J.S. Denker, (1994). “Adiabatic Dynamic Logic”, Proceedings of the IEEE Custom Integrated Circuits Conference (CICC'94), pages 282-285.

[11]. W.Y. Wang and K.T. Lau, (1995). “Adiabatic pseudodomino logic”, Electronics Letters, 31(23): pages 1982- 1983.

[12]. D. Maksimovic, V.G. Oklobdzija, B. Nikolic and K.W. Current, (1997). “Clocked CMOS Adiabatic Logic with Integrated Single-Phase Power-Clock Supply: Experimental Results”, Proceedings of the 1997 International Symposium on Low Power Electronics and Design (ISLPED'97), pages 323-327.

[13]. Yong Moon and Deog-Kyoon Jeong, (1996). “An efficient charge recovery logic circuit”, IEEE Journal of Solid-State Circuits, 31(4):514-522.

[14]. A. Kramer, J.S. Denker, B. Flower and J. Moroney, (1995). “2nd Order adiabatic computation with 2n-2p and 2n-2n2p logic circuits”, Proceedings of IEEE Symposium Low Power Design (ISLPD'95), pp. 191-196.

[15]. D. Mateo and A. Rubio, (1996). “Quasi-adiabatic ternary CMOS logic”, Electronics Letters, 32(2): 99 – 101.

[16]. A. Vetuli, S.D. Pascoli and L.M. Reyneri, (1996). “Positive feedback in adiabatic logic”, Electronics Letters, 32(20):1867-1869.

[17]. V.K. De and J.D. Meindl, (1996a). “Complementary Adiabatic and Fully Adiabatic MOS Logic Families for Gigascale Integration”, 43rd IEEE International Solid State Circuits Conference – Digest of Technical Papers, pages 300-301 and 462.

[18]. V.K. De and J.D. Meindl, (1996b). “Opportunities for non-dissipative computation [adiabatic logic]”, Proceedings of 9th annual IEEE ASIC Conference and Exhibit, pages 297-300.

[19]. V.G. Oklobdzija, D. Maksimovic and Fengcheng Lin, (1997). “Pass-Transistor Adiabatic Logic Using Single Power- Clock Supply”, IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing, 44(10):842-846.

[20]. Y. Ye, K. Roy and G.I. Stamoulis, (1997). “Quasi-Static Energy Recovery Logic and Supply-Clock Generation Circuits”, Proceedings of the 1997 International Symposium on Low Power Electronics and Design (ISLPED'97), pages 96-99.

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* Research Scholar, S.V.U College of Engineering, Tirupati

** Professor of ECE, S.V.U College of Engineering, Tirupati

T. Surendra Nath* , V. Kalpana, Vijaya Kishore*

* PG Student, Communication Systems, SITAMS, Chittoor

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ECE Department, EVMCET, AP, India

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ECE Department, JNTUH, Hyderabad, A.P, India.

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Department of Electronics Engineering

Indian School of Mines Dhanbad, India.

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* PG Student, Communication Systems, SITAMS, Chittoor.

PG Student, Communication Systems, SITAMS, Chittoor.

* Professor, Department of ECE, SITAMS, Chittoor.

A. Kishore Kumar* , D. Somasundareswari, V.Duraisamy*****

* Dean, Electrical Sciences, Adithya Institute of Technology, Coimbatore, India.

* Professor & Principal, Hindustan College of Engineering & Technology, Coimbatore, India.

** Assistant Professor, ECE Department, Coimbatore Institute of Technology, Coimbatore, India.