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April 2007, Volume 16, Number 1

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J. Dobes, K. Ulovec [references] [full-text] [Download Citations]
Modeling Delays of Microwave Transistors and Transmission Lines by the 2nd Order Bessel Function

At present, most of simulation programs can characterize gate delays of microwave transistors. However, the delay is mostly approximated by means of first-order differential equations. In the paper, a more accurate way is suggested which is based on an appropriate second-order differential equation. Concerning the transmission line delay, majority of the simulation programs use both Branin (for lossless lines) and LCRG (for lossy lines) models. However, the first causes extreme simulation times, and the second causes well-known spurious oscillations in the simulation results. In the paper, an unusual way for modeling the transmission line delay is defined, which is also based on the second-order Bessel function. The proposed model does not create the spurious oscillations and the simulation times are comparable with those obtained with the classical models. Properties of the implementation of the second-order Bessel function are demonstrated by analyses of both digital and analog microwave circuits.

  1. MASSOBRIO, G., ANTOGNETTI, P. Semiconductor Device Modeling With SPICE. 2nd ed. New York: McGraw-Hill, 1993.
  2. VLADIMIRESCU, A. The Spice Book. 1st ed. New York: John Wiley & Sons, 1994.
  3. MADJAR, A. A fully analytical AC large-signal model of the GaAs MESFET for nonlinear network analysis and design. IEEE Transactions on Microwave Theory and Techniques, 1988, vol. 36, no. 1, p. 61 - 67.
  4. GUO, Y.-S. Transient simulation of high-speed interconnects based on the semidiscretization of telegrapher's equations. IEEE Transactions on Computer-Aided Design, 2002, vol. 21, no. 7, p. 799 - 809.
  5. DIVINA, L., SKVOR, Z. The distributed oscillator at 4 GHz. IEEE Transactions on Microwave Theory and Techniques, 1998, vol. 46, no. 12, p. 2240 - 2243.
  6. TAJIMA, Y., WRONA, B., MISHIMA, K. GaAs FET large-signal model and its application to circuit designs. IEEE Transactions on Electron Devices, 1981, vol. 28, no. 2, p. 171 - 175.
  7. SUSSMAN-FORT, S. E., HANTGAN, J. C., HUANG, F. L. A SPICE model for enhancement- and depletion-mode GaAs FET's. IEEE Transactions on Microwave Theory and Techniques, 1986, vol. 34, no. 11, p. 1115 - 1119.

Keywords: Bessel function, ordinary differential equations, group delay, MESFET, gate delay, transmission line

K. Zaplatilek, P. Ziska, K. Hajek [references] [full-text] [Download Citations]
Practice Utilization of Algorithms for Analog Filter Group Delay Optimization

This contribution deals with an application of three different algorithms which optimize a group delay of analog filters. One of them is a part of the professional circuit simulator Micro Cap 7 and the others two original algorithms are developed in the MATLAB environment. An all-pass network is used to optimize the group delay of an arbitrary analog filter. Introduced algorithms look for an optimal order and optimal coefficients of an all-pass network transfer function. Theoretical foundations are introduced and all algorithms are tested using the optimization of testing analog filter. The optimization is always run three times because the second, third and fourth-order all-pass network is used. An equalization of the original group delay is a main objective of these optimizations. All outputs of all algorithms are critically evaluated and also described.

  1. POWELL, M. J. D. An efficient method for finding the minimum of a function of several variables without calculating derivatives. Computer Journal, 1964, no. 7, p. 155-162.
  2. SHAUMAN, R., GHAUSI, M. S., LAKER, K. R. Design of Analog Filters. Prentice Hall, New Jersey, 1990.
  3. HUYNEN, I., VANHOENACKER-JANVIER, D., VANDER VORST, A. Spectral domain form of new variational expression for very fast calculation of multilayered lossy planar line parameters. IEEE Transactions on Microwave Theory and Techniques, 1994, vol. 42, no. 11, p. 2099-2106.
  4. STORN, R. Differential evolution design of an IIR-filter with requirements for magnitude and group delay. Technical Report TR-95-026, ICSI, May 1995.
  5. TAYLOR, F. J., WILLIAMS, A. B. Electronic Filter Design Handbook. McGraw-Hill, 1995.
  6. NELDER, J. A., MEAD, R. A simplex method for function minimalization. Computer Journal, 1964, vol. 7, pp. 308-313.
  7. MICHALEWICZ, Z. Genetic Algorithms + Data Structures = Evolution Programs. 3rd ed. Berlin, Heidelberg, New York: Springer-Verlag, 1996.
  8. SCULTETY, L. Zero group delay networks. In. Proc. of the ECCTD'97. Budapest (Hungary), September 1997, p. 589-593.
  9. MARTINEK, P., BORES, P., MATZNER, I. Electric filters. CVUT Prague, 1998. ISBN 80-01-01591-2 (in Czech).
  10. CARVALHO, D. B., FILHO, S. N., SEARA, R. Design of phase equalizers using phase delay characteristic. In Proc. of the ISCAS'98, Monterey (USA), 1998.
  11. LAGARIAS, J. C., REEDS, J. A., WRIGHT, M. H., WRIGHT, P. E. Convergence properties of the Nelder-Mead Simplex Method in low dimensions. SIAM Journal of Optimization, 1998, vol. 9, no. 1, p. 112-147.
  12. WANG, S., WANG, F., DEVABHAKTUNI, V. K., ZHANG, Q. J. A hybrid neural and circuit-based model structure for microwave modeling. In Proceedings of the 29th European Microwave Conference. Munich (Germany), 1999, p. 174 - 177.
  13. GREGORA, P., VIT, V. Television Techniques. Devices for TV Signal Transmission. Prague: BEN Technical Literature, 2000 (in Czech).
  14. ZISKA, P., LAIPERT, M. Analog group delay equalizers design based on evolutionary algorithm. Radioengineering, 2006, vol. 15, no. 1, p. 1-5, ISSN 1210-2512.
  15. MARTINEK, P., VONDRAS, J. New approach to filters and group delay equaliser transfer function design. In ICECS 2001 - The 8th IEEE International Conference on Electronics, Circuits and Systems. St. Julian's: ICECS 2001, 2001, vol. 1, p. 157-160.Julian's: ICECS 2001, 2001, vol. 1, p. 157-160.
  16. POWELL, M. J. D., SCHOLTES, S. System modelling and optimization:Methods, theory and applications. In The 19th IFIP TC7 Conferenceon System Modelling and Optimization. Cambridge (UK):Kluwer 2000.
  17. HAJEK, K., SEDLACEK, J. Frequency Filters. Prague: BENTechnicalLiterature, 2002. ISBN 80-7300-023-7 (in Czech).
  18. ZELINKA, I. Artificial Intelligence in Global Optimization Problems.Prague: BEN-Technical Literature, 2002 (in Czech).
  19. BUCKNER, M. A. Learning from Data with Localized Regressionand Differential Evolution. Dissertation Thesis, University of Tennessee,Knoxville, May 2003.
  20. ZAPLATILEK, K., HAJEK, K.: Efficient algorithm for group delayequalization of analog filters. In GSPx International Signal ProcessingConference. Dallas (Texas, USA), 2003 (CD-ROM).
  21. MATHEWS, J. H., FINK, K. K. Numerical Methods Using Matlab.4th ed. Prentice-Hall, Inc., 2004. ISBN 0-13-065248-2.
  22. BIOLEK, D., BIOLKOVA, V. Three-CDTA current-mode biquad.WSEAS Transactions on Circuits, 2005, vol. 4, no. 10, p. 1227 to1232. ISSN 1109-2734.
  23. ZISKA, P., LAIPERT, M. Novel design method of analog all-passfilters. In ISSCS 2005 - Proceedings. Iasi: Technical University,2005, vol. 1, p. 331-334. ISBN 0-7803-9029-6.
  24. Micro-Cap 7,
  25. Fairchild Semiconductor web sites:
  26. KR Electronics web sites:

Keywords: Analog filters, group delay, optimization, all-pass networks, MATLAB, Micro-Cap, evolutionary algorithms

S. K. Parui, S. Das [references] [full-text] [Download Citations]
A New Defected Ground Structure for Different Microstrip Circuit Applications

In this paper, a microstrip transmission line combined with a new U-headed dumb-bell defected ground structure (DGS) is investigated. The proposed DGS of two U-shape slots connected by a thin transverse slot is placed in the ground plane of a microstrip line. A finite cutoff frequency and attenuation pole is observed and thus, the equivalent circuit of the DGS unit can be represented by a parallel LC resonant circuit in series with the transmission line. A two-cell DGS microstrip line yields a better lowpass filtering characteristics. The simulation is carried out by the MoM based IE3D software and in the experimental measurements a vector network analyzer is used. The effects of the transverse slot width and the distance between arms of the U-slot on the filter response curve are studied. This DGS is utilized for different microstrip circuit applications. The DGS is placed in the ground of a capacitive loaded microstrip line and a very low cutoff frequency is obtained. The DGS is adopted under the coupled lines of a parallel line coupler and an improvement in coupling coefficient is noticed. The proposed DGS is also incorporated in the ground plane under the feed lines and the coupled lines of a bandpass filter to improve separately the stopband and passband performances.

  1. YABLONOVITCH, E. Photonic crystals. J. Modern Opt., 1994, vol. 41, no. 2, p. 173 - 194.
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  3. PARUI, S. K., DAS, S. A simple electromagnetic bandgap structure for microstrip line. In Proceedings of the IEEE India Annual Conference. 2004, p. 547 - 548.
  4. AHN, D., PARK, J. S., KIM, C. S., KIM, J., QIAN, Y., ITOH, T. A design of the low-pass filter using the novel microstrip defected ground structure. IEEE Trans. Microwave Theory Tech., 2001, vol. 49, no. 1, p. 86 - 93.
  5. KIM, C. S., PARK, J. S., AHN, D., LIM, J. B. A novel 1-D periodic defected ground structure for planar circuits. IEEE Microwave Guided Wave Lett., 2000, vol. 10, no. 4, p. 131 - 133.
  6. LIM, J. S., KIM, C. S., LEE, Y. T., AHN, D., NAM, S. Design of lowpass filters using defected ground structure and compensated microstrip line. IEE Electronics Lett., 2002, vol. 38, no. 22, p. 1357 to 1358.
  7. LIU, H., LI, Z. Enhanced Hi-Lo microstrip lowpass filter using nonuniform defected ground structure (DGS) slots. J. of Active and Passive Electronic Devices, 2005, vol. 1, p. 35-40.
  8. ABDEL-RAHMAN, A. B., VERMA, A. K., BOUTEJDAR, A., OMAR, A. S. Control of bandstop response of Hi-Lo microstrip low-pass filter using slot in ground plane. IEEE Trans. Microwave Theory Tech., 2004, vol. 52, no. 3, p. 1008 - 1013.
  9. LIU, H., LI, Z., SUN, X., Compact defected ground structure in microstrip technology. IEE Electronics Lett., 2005, vol. 41, no. 3, p. 132 - 134.
  10. KARIM, M. F., LIU, A. Q., ALPHONES, A., J. ZHANG, X., YU, A. B., CPW Band-stop filter using unloaded and loaded EBG structures. IEE Proc. Microwave Antenna Propagation, 2005, vol. 52, no. 6, p. 434 - 440.
  11. KO, Y-J., PARK, J-Y., BU, J-U. Fully integrated unequal Wilkinson power divider with EBG CPW. IEEE Microwave and Wireless Components Lett., 2003, vol.,13, no. 7, p.,276 - 278.
  12. KIM, C-S., KIM, D-H., SONG, I-S., LEONG, K. H., ITOH, T., AHN, D. A design of a ring bandpass filters with wide rejection band using DGS and spur-line coupling structures. In Proceedings of IEEE Conference. 2005, p. 2183-2186.
  13. HONG, JIA-SHEN., G., LANCASTER, M. J. Microstrip Filters for RF/Microwave Applications. John Willey & Sons, Inc., 2001.

Keywords: Defected ground structure (DGS), microstrip, lowpass filter, bandpass filter, coupler

L. Merad, F. T. Bendimerad, S. M. Meriah, S. A. Djennas [references] [full-text] [Download Citations]
Neural Networks for Synthesis and Optimization of Antenna Arrays

This paper describes a usual application of back-propagation neural networks for synthesis and optimization of antenna array. The neural network is able to model and to optimize the antennas arrays, by acting on radioelectric or geometric parameters and by taking into account predetermined general criteria. The neural network allows not only establishing important analytical equations for the optimization step, but also a great flexibility between the system parameters in input and output. This step of optimization becomes then possible due to the explicit relation given by the neural network. According to different formulations of the synthesis problem such as acting on the feed law (amplitude and/or phase) and/or space position of the radiating sources, results on antennas arrays synthesis and optimization by neural networks are presented and discussed. However ANN is able to generate very fast the results of synthesis comparing to other approaches.

  1. STUZMAN, W. L., THIELE, C. Antenna Theory and Design. John Wiley & Sons, 1981.
  2. SHAVIT, R., TAIG, I. Comparison study of pattern-synthesis techniques using neural networks. Microwave and Optical Technology Letters, 2003, vol. 42, no.2, pp. 175-179.
  3. REZA, S., CHRISTODOULOU, C. G. Beam shaping with antennas arrays using neural netsworks. In IEEE SouthEast Conf., Orlando (Florida), April 1998.
  4. EL ZOOGHBY, A. H, CHRISTODOULOU, C. G., GEORGIOPOULOS, M. Neural network-based adaptive beamforming for one- and two-dimensional antenna arrays. IEEE Transaction on Antennas and Propagation, 1998, vol 46, no.12, pp. 1891-1893.
  5. GHAYOULA, R., TRAII, M., GHARSALLAH, A. Application of neural networks to the synthesis of multibeam antenna arrays. World enformatika Society, Transaction on Engineering Computing and Technology, 2006, vol. 14, pp. 270-273.
  6. MIKAVICA, M., NESIC, A. CAD for Linear and Planar Antenna Arrays of Various Radiating Elements. Artech House, Inc., 1992.
  7. GOLDBERG, D. E. Genetic Algorithm Search, Optimisation and Machine Learning. Addison-Wesley, 1994.
  8. JOHNSON, M., SAMI, R. Genetic algorithm optimization for aerospace electromagnetic design and analysis. IEEE Transaction on Antennas and Propagation, 1996, pp. 87-102.
  9. MERAD, L., MERIAH, S. M., BENDIMERAD, F. T. Optimisation par l'algorithme genetique de reseaux d'antennes imprimees. In Conference sur le Genie Electrique, CGE' 01, Recueil sur CDROM, December 2001 (in French).
  10. HAYKIN, S. Neural Networks: A Comprehensive Foundation. Prentice Hall, 1999.
  11. TAIRIA, S., LECHEVALIER, Y., GASCUEL, O., CANU, S. Statistiques et methodes neuronales. Dunod, 1997 (in French).
  12. ANTOGNETTI, P., MILUTINOVIC, V. Neural Networks Concept and Implementations. Prentice Hall, vol. 2, 1991.
  13. CHEN, S., COWAN, C. F. N., GRANT, P. M. Orthogonal least squares learning algorithms for Radial Basis Function Networks. IEEE Transactions on Neural Networks, 1991, vol. 2, no.2, pp. 302-309.
  14. DAMIANO, J. P. Contribution a l'etude des antennes microrubans multicouches a elements superposes ou decales. PhD Thesis, Universite de Nice-Sophia Antipolis, France, 1989 (in French).
  15. LIPPMANN, R. P. An introduction to computing with neural nets. IEEE, ASSP magazine, April 1987.
  16. MULLER, B., REINHARDT, J., STRICKLAND, M. T. Neural Networks: An Introduction. Springer-Verlang, 1995.
  17. MERAD, L., MERIAH, S. M., BENDIMERAD, F. T. Modelisation et optimisation par les reseaux de neurones de reseaux d'antennes imprimees. Journees des Mathemetiques Appliquees, JMA' 2000, Recueil sur CDROM, November 2000 (in French).
  18. DEMUTH, H., BEALE, M. Neural Network Toolbox for Use with Matlab. Users Guides, Mathworks, 1997.
  19. YAN, K. K., LU, Y. Sidelobe reduction in array-pattern synthesis using genetic algorithm. IEEE Transaction on Antennas and Propagation, 1997, vol. 45, no.7, pp. 1117-1121.
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Keywords: Neural networks, modeling, optimization, synthesis, antennas arrays, printed antenna

A. Mohammed, T. Hult [references] [full-text] [Download Citations]
The Effects of MIMO Antenna System Parameters and Carrier Frequency on Active Control Suppression of EM Fields

In this paper we propose a new approach employing adaptive active control algorithms combined with a Multiple-Input Multiple-Output (MIMO) antenna system to suppress the electromagnetic field at a certain volume in space (e.g., at the human head). We will investigate the effects of the size and number of MIMO antenna elements on the system performance and test the algorithms at different carrier frequencies (e.g., GSM bands and UMTS).

  1. WIDROW, B., STEAMS, S. D. Adaptive Signal Processing. Prentice-Hall, 1985.
  2. KUO, S. M., MORGAN, D. R. Active Noise Control Systems. John Wiley & Sons Inc., 1996.
  3. JOHANSON, S. Control of Propeller-Induced Noise in Aircraft. Doctoral Thesis, Blekinge Institute of Technology, 2000.
  4. HULT, T., MOHAMMED, A., NORDEBO, S. Active suppression of electromagnetic fields using a MIMO antenna system. In Proc. of the 17th Int. Conf. on Applied Electromagnetics and Communications, ICECom 2003, 2003.
  5. HULT, T., MOHAMMED, A. Suppression of EM fields using active control algorithms and MIMO antenna system. Radioengineering, 2004, vol. 13, no. 3, pp. 22-25.

Keywords: Electromagnetic fields, Adaptive Active Control Algorithms, Multiple-input multiple-output (MIMO) antenna systems, radio wave propagation

F. Jelinek, J. Saroch, O. Kucera, J. Hasek, J. Pokorny, N. Jaffrezic-Renault, L. Ponsonnet [references] [full-text] [Download Citations]
Measurement of Electromagnetic Activity of Yeast Cells at 42 GHz

This paper discusses the possibility of using a device composed of a resonant cavity, preamplifiers, and a spectrum analyzer to detect electromagnetic emission of yeast cells at a frequency of about 42 GHz. Measurement in this frequency range is based on the Frohlich\'s postulate of coherent polar oscillations as a fundamental biophysical property of biological systems and on the experiments of Grundler and Keilmann who disclosed effects of exposure to the electromagnetic field at 42 GHz on the growth rate of yeast cells. This article includes a detailed description of the laboratory equipment and the methods used to evaluate the obtained results.

  1. FROHLICH, H. Quantum mechanical concepts in biology. In Theoretical Physics and Biology, Marois, M., Ed. North Holland, Amsterdam 1969. p. 13 - 22. (Proc. 1st Intern. Conf. on Theoretical Physics and Biology, Versailles 1967).
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  4. POKORNY, J., HASEK, J., JELINEK, F. Electromagnetic field in microtubules: Effects on transfer of mass particles and electrons. J. Biol. Phys. 2005, vol. 31, p. 501 - 514.
  5. POKORNY, J., HASEK, J., JELINEK, F. Endogenous electric field and organization of living matter. Electromag. Biol. Med. 2005, vol. 24, p. 185 - 197.
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  7. ROWLANDS, S. The interaction of living red blood cells. In Biological Coherence and Response to External Stimuli, Frohlich, H. Ed. Springer, Berlin, Heidelberg, New York, 1988, p. 171 - 191.
  8. LEVIN, A., KORENSTEIN, R. Membrane fluctuations in erythro-cytes are linked to MgATP-dependent dynamic assembly of the membrane skeleton. Biophys. J. 1991, vol. 60, no. 3, p. 733 - 737.
  9. ALBRECHT-BUEHLER, G. Rudimentary form of cellular 'Vision'. Proc. Natl. Acad. Sci. U.S.A.. 1992, vol. 89, p. 8288 - 8293.
  10. VOS, M.H., RAPPAPORT, F., LAMBRY, J.C., BRETON, J., MARTIN, J.-L. Visualization of coherent nuclear motion in a membrane protein by femtosecond spectroscopy. Nature. 1993, vol. 363, p. 320 - 325.
  11. PELLING, A.E., SEHATI, S., GRALLA, E.B., VALENTINE, J.S., GIMZEWSKI, J.K. Local Nanomechanical Motion of the Cell Wall of Sacch. cerevisiae. Science. 2004, vol. 305, p. 1147-1150.
  12. PELLING, A.E., SEHATI, S., GRALLA, E.B., GIMZEWSKI, J.K. Time dependence of the frequency and amplitude of the local nanomechanical motion of yeast. Nanomedicine: Nanotechnology, Biology, and Medicine. 2005, vol. 1, p. 178 - 183.
  13. GRUNDLER, W., KEILMANN, F., PUTTERLIK, V., SANTO, L., STRUBE, D., ZIMMERMANN, I. Nonthermal resonant effects of 42 GHz Microwaves on the growth of yeast cultures. In Coherent Excitation in Biological Systems, Frohlich, H., Kremer, F. Eds. Springer, Berlin, 1983, p. 21 - 37.
  14. JELINEK, F., POKORNY, J., HASEK, J., SAROCH, J. Experimental investigation of electromagnetic activity of yeast cells at millimeter waves. Electromagnetic Biology and Medicine. 2005, vol. 24, p. 301 - 307.
  15. POKORNY, J., HASEK, J., JELINEK, F., SAROCH, J., PALAN, B. Electromagnetic activity of yeast cells in the M phase. Electro- and Magnetobiology. 2001, vol. 20, p. 371 - 396.
  16. KUCERA, O. Measurement of Electromagnetic Activity of Yeast Cells in mm Wave range. Bachelor's thesis (in Czech). CTU in Prague, FEE, Department of Electromagnetic Field. Praha, 2006.

Keywords: Millimeter wave measurement, electromagnetic activity of cell, cellular biophysics

R. Dolecek, K. Hlava [references] [full-text] [Download Citations]
Transient Effects at Power-Supply System of the Czech Railways from EMC Viewpoint

The paper deals with the behavior of the traction power-supply system 25 kV, 50 Hz at the Czech Railways. Electrical conditions on a contact line affect electrical conditions in a feeding station. This relation represents galvanic coupling from EMC viewpoint. Explanation of transient effects during short-circuits at the contact line can be considered as the main problem. These effects can arise during a failure in a traction circuit. Therefore, the attention is turned to an adjustment protection design of the traction circuit. Simulation diagrams were created. The design can be utilizable for a feeding station with Filter-Compensation Equipment, which is designed for the EMI reduction.

  1. HLAVA, K. Restriction of FCE effect to centralized ripple control of electric energy contractor, Part 1 and 2. Report no. D 237 4026, TCTR, Department EMC, Prague, 1996 (in Czech).
  2. HLAVA, K. Design of addition of Filter-compensation equipment to feeding stations at Czech Railways. Report no. Z 0024 003, "Control branch of Filter-compensation equipment" (BK 22 459), Prague, 1994 (in Czech).
  3. PNE 38 2530 Centralized ripple control: Automatics, transmitters and receivers (in Czech).
  4. HLAVA, K. Diagnostic of power-supply system effect at Czech Railways to centralized ripple control. Scientific Technical Proceeding of Czech Railways. 2000, no. 10, ISSN 1214-9047 (in Czech).
  5. LETTL, J., FLIGL, S. High-level EMC at matrix converter AC/AC energy conversion. In ELEN Proceedings, 2006, part 5, Prague, ISBN 80-239-7650-8.
  6. LETTL, J., FLIGL, S. Electromagnetic compatibility of matrix converter system. Radioengineering, 2006, vol. 15, no. 4, ISSN 1210-2512.
  7. VERZICH, V. Feeding systems of Railway interlock devices. TC CR, Prague, 2005, ISBN 80-85104-86-5 (in Czech).
  8. RAMO, S., WHINNERY, R. J., DUZER, V. T. Fields and Waves in Communication Electronics. Canada, 1993, ISBN 0-471-58551-3.
  9. BURRTSCHER, H. Laboratory Model to Examine Extension and Superposition of High Frequency at Railway Network. Co-operator at Institution for AIE, ETH Zurich, ORE A 122, part 3.2 Work program (in German).
  10. HLAVA, K. Electromagnetic Compatibility of Railway Devices. University of Pardubice, 2004, ISBN 80-7194-637-0 (in Czech).
  11. BAZELYAN, M. E., RAIZER, P. Yu. Spark Discharge. New York: CRC Press LLC, USA, 1998, ISBN 0-8493-2868-3.
  12. EN 50 122-2/A1: Railway devices - Stationary tractive devices - Part 2: Protecting measures from effects of dispersion currents witch are bring out by DC traction systems.
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  14. HLAVA, K. Analysis of conditions of FCE for feeding station of Czech Railways Modrice. Prague, Report no.11, 2005 (in Czech).
  15. NAHVI, M., EDMINISFER, J. Electric Circuits, McGraw-Hill, USA, 2003, ISBN 0-07-139309-2.

Keywords: Power-supply system, power supply line, Filter-Compensation Equipment, feeding station, contact line, transient effect, harmonic branch, short-circuit

P. Foris, D. Levicky [references] [full-text] [Download Citations]
Implementations of HVS Models in Digital Image Watermarking

In the paper two possible implementations of Human Visual System (HVS) models in digital watermarking of still images are presented. The first method performs watermark embedding in transform domain of Discrete Cosine Transform (DCT) and the second method is based on Discrete Wavelet Transform (DWT). Both methods use HVS models to select perceptually significant transform coefficients and at the same time to determine the bounds of modification of selected coefficients in watermark embedding process. The HVS models in DCT and DWT domains consist of three parts which exploit various properties of human eye. The first part is the HVS model in DCT (DWT) domain based on three basic properties of human vision: frequency sensitivity, luminance sensitivity and masking effects. The second part is the HVS model based on Region of Interest (ROI). It is composed of contrast thresholds as a function of spatial frequency and eye\'s eccentricity. The third part is the HVS model based on noise visibility in an image and is described by so called Noise Visibility Function (NVF). Watermark detection is performed without use of original image and watermarks have a form of real number sequences with normal distribution zero mean and unit variance. The robustness of presented perceptual watermarking methods against various types of attacks is also briefly discussed.

  1. LEVICKY, D., FORIS, P., KLENOVICOVA, Z., RIDZON, R. Digital right management. In Research in Telecommunication Technology 2005. 6th Int. Conf. RTT 2005, 2005.
  2. PETERSON, H. A., AHUMADA, A. J., WATSON, A. B. An improved detection model for DCT coefficient quantization. In Proc. SPIE Conf. Human Vision, 1993, vol. 1913, p.191 - 201.
  3. VOLOSHYNOVSKIY, S., HERRIGEL, A., BAUMGARTNER, N., PUN, T. A stochastic approach to content adaptive digital image watermarking. In Proceedings of the Third International Workshop on Information Hiding, 1999, p.211-236.
  4. WANG, Z., BOVIK, A. C. Foveation scalable video coding with automatic fixation selection. IEEE Transactions on Image Processing, 2003, vol. 12, no. 2, p. 1 - 12.
  5. WATSON, A. B. DCT quantization matrices visually optimized for individual images. In Proc. SPIE Conf. Human Vision, 1993, vol. 1913, p. 202 - 216.
  6. WATSON, A. B., YANG, G. Y., SOLOMON, J. A., VILLASENOR, J. Visibility of wavelet quantization noise. IEEE Trans. of Image Processing, 1997, vol. 6, p. 1164 - 1175.

Keywords: Digital image watermarking, human visual system models, discrete cosine transform, discrete wavelet transform, noise visibility function, watermark embedding, watermark detection

M. Oravec, J. Pavlovicova [references] [full-text] [Download Citations]
Face Recognition Methods Based on Feedforward Neural Networks, Principal Component Analysis and Self-Organizing Map

In this contribution, human face as biometric is considered. Original method of feature extraction from image data is introduced using MLP (multilayer perceptron) and PCA (principal component analysis). This method is used in human face recognition system and results are compared to face recognition system using PCA directly, to a system with direct classification of input images by MLP and RBF (radial basis function) networks, and to a system using MLP as a feature extractor and MLP and RBF networks in the role of classifier. Also a two-stage method for face recognition is presented, in which Kohonen self-organizing map is used as a feature extractor. MLP and RBF network are used as classifiers. In order to obtain deeper insight into presented methods, also visualizations of internal representation of input data obtained by neural networks are presented.

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Keywords: Biometrics, face recognition, neural networks, PCA, multilayer perceptron, radial-basis function network, self-organizing map, visualization, LDA, kernels

J. Mihalik, V. Michalcin [references] [full-text] [Download Citations]
Animation of 3D Model of Human Head

The paper deals with the new algorithm of animation of 3D model of the human head in combination with its global motion. The designed algorithm is very fast and with low calculation requirements, because it does not need the synthesis of the input videosequence for estimation of the animation parameters as well as the parameters of global motion. The used 3D model Candide generates different expressions using its animation units which are controlled by the animation parameters. These ones are estimated on the basis of optical flow without the need of extracting of the feature points in the frames of the input videosequence because they are given by the selected vertices of the animation units of the calibrated 3D model Candide. The established multiple iterations inside the designed animation algorithm of 3D model of the human head between two successive frames significantly improved its accuracy above all for the large motion.

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Keywords: Animation, 3D model, human head, animation parameters, global motion, local motion, optical flow, estimation

Z. Chaloupka, J. Uhlir [references] [full-text] [Download Citations]
Speech Defect Analysis Using Hidden Markov Models

The main aim of this paper is the analysis of speech deteriorated by a very rare disease, which induce epileptic seizures in a part of brain responsible for speech production. Speech defects, represented mostly by the combination of missing and mismatched phonemes, are sought and examined in the spectral and time domain.
An algorithm, proposed in this paper, is based on Hidden Markov Models (HMMs) and it is most suitable for the speech recognition tasks. The algorithm is able to analyze in both time and spectral domains simultaneously; in the spectral domain as a log-likelihood score and in the time domain as a forced time alignment of the HMMs.
The suggested algorithm works properly in the time domain. The results for the spectral domain are not credible, because the algorithm have to be tested on more data (not available at the time of paper preparation).

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Keywords: Speech defects, LKS, developmental dysphasia, HMMs, speech recognition, forced time alignment