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Proceedings of Czech and Slovak Technical Universities

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September 2004, Volume 13, Number 3

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J. Novotny, P. Sovka, J. Uhlir [references] [full-text] [Download Citations]
Study and Application of Silence Model Adaptation for Use in Telephone Speech Recognition System

This paper addresses the problem of the mismatch between a silence model and background noises which often occurs in a telephone speech recognition system (SRS) application. At first, the use of parallel model combination (PMC) methods is studied with the respect to this application. Secondly, the effective adaptation of a silence model to various background noises is confirmed. Finally, an original method combining log-add PMC with a noise power spectral density estimation based on minimum statistics is proposed. The performed tests prove the benefit of the suggested method to the speech recognition results that is caused by the stability of speech vector selection under the influence of various background noises. The advantages can be seen in no extra voice activity detector and in a relatively low computational load.

  1. CERNOCKY , J., POLLAK, P., HANZL, V. Czech Recordings andAnnotations on CD's - Documentation on the Czech Database andDatabase Access. Research Report, Prague, CTU, 2000.
  2. HILGER, F., NEY, H. Noise level normalization and reference adaptationfor robust speech recognition. In Proc. ASR, 2000, p. 64-68.
  3. RAMAN, V., RAMANUJAM, V. Robustness issues and solutions inspeech recognition based telephony services. In Proc. ICASSP, 1997,p. 1523-1526.
  4. JUNQUA, J. C., MAK, B., REAVES, B. A robust algorithm for wordboundary detection in the presence of noise. IEEE Trans. on Speech andAudio Processing, 1994, vol. 2, p. 406-412.
  5. VETH, J., MAUUARY, L., NOE, B., WET, F., SIENEL J., BOVES,L., JOUVET, D. Feature vector selection to improve ASR robustness innoisy conditions. In Proc. Eurospeech, 2001.
  6. ETSI ES 202 050 V1.1.1. European Telecommunication Standards Institute,2002.
  7. ACCAINO, S., TSIPORKOVA, E., HAMME, H. Modeling of extraevents for telephony. In Voice operated telecom services: Do they have abright future? workshop proceedings, Ghent, Belgium, 2000, p. 75-78.
  8. NOVOTNY, J., SOVKA, P., UHL´IR· , J. Analysis and Optimizationof Telephone Speech Command Recognition System Performance inNoisy Environment. Radioengineering, 2004, vol. 13.
  9. GALES, M. J. F., YOUNG, S.J. HMM recognition in noise using parallelmodel combination. In Proc. Eurospeech, 1993, p. 837-840.
  10. GALES, M. J. F., YOUNG, S.J. A fast and flexible implementation ofparallel model combination. In Proc. ICASSP, 1995, pp. 133-136.
  11. GALES, M. J. F. Predictive model-based compensation schemes for robustspeech recognition. Speech Communication, 1998, vol. 25.
  12. HWANG, T. H., WANG, H. Ch. A fast algorithm for parallel modelcombination for noisy speech recognition. Computer Speech and Language,2000, vol. 14, p. 81-100.
  13. HUNG, J., SHEN, J., LEE, L. New approaches for domain transformationand parameter combination for improved accuracy in parallel modelcombination (PMC) techniques. IEEE Trans. on Speech and Audio Processing,2001, vol. 9, p. 842-855.
  14. MARTIN, R. Spectral subtraction based on minimum statistics. In Proc.Eur. Signal Processing Conference, 1994, p. 1182-1185.
  15. MARTIN, R. Noise power spectral density estimation based on optimalsmoothing and minimum statistics. IEEE Trans. on Speech and AudioProcessing, 2001, vol. 9, p. 504-512.
  16. YOUNG, S. The HTK Book (for HTK Version 3.1). Cambridge UniversityEngineering Department, December 2001.

J. Dobes, L. Pospisil [references] [full-text] [Download Citations]
Enhancing the Accuracy of Microwave Element Models by Artificial Neural Networks

In the recent PSpice programs, five types of the GaAs FET model have been implemented. However, some of them are too sophisticated and therefore very difficult to measure and identify afterwards, especially the realistic model of Parker and Skellern. In the paper, simple enhancements of one of the classical models are proposed first. The resulting modification is usable for the accurate modeling of both GaAs FETs and pHEMTs. Moreover, its updated capacitance function can serve as an accurate representation of microwave varactors, which is also important. The precision of the updated models can be strongly enhanced using the artificial neural networks. In the paper, both using an exclusive neural network without an analytic model and cooperating a corrective neural network with the updated analytic model will be discussed. The accuracy of the analytic models, the models based on the exclusive neural network, and the models created as a combination of the updated analytic model and the corrective neural network will be compared.

  1. 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.
  2. CURTICE, W. R. GaAs MESFET modeling and nonlinear CAD.IEEE Transactions on Microwave Theory and Techniques, 1988,vol. 36, no. 2, p. 220 - 230.
  3. PARKER, A. E., SKELLERN, D. J. A realistic large-signal MESFETmodel for SPICE. IEEE Transactions on Microwave Theory andTechniques, 1997, vol. 45, no. 9, p. 1563 - 1571.
  4. STATZ, H., NEWMAN, P., SMITH, I. W., PUCEL, R. A.,HAUS, H. A. GaAs FET device and circuit simulation in SPICE.IEEE Transactions on Electron Devices, 1987, vol. 34, no. 2,p. 160 - 169.
  5. JASTRZEBSKI, A. K. Non-linear MESFET modeling. In Proceedingsof the 17th European Microwave Conference EuMC, 1987,p. 599 - 604.
  6. DOBES, J. C.I.A.-a comprehensive CAD tool for analog, RF,and microwave IC's. In Proceedings of the 8th IEEE InternationalSymposium on High Performance Electron Devices for Microwaveand Optoelectronic Applications EDMO, Glasgow (UK),2000, p. 212 - 217.
  7. DOBES, J. Expressing the MESFET and transmission line delays usingBessel function. In Proceedings of the 16th European Conferenceon Circuit Theory and Design, Krak´ow (Poland), 2003, p. 169 - 172.
  8. MADJAR, A. A fully analytical AC large-signal model of the GaAsMESFET for nonlinear network analysis and design. IEEE Transactionson Microwave Theory and Techniques, 1988, vol. 36, no. 1,p. 61 - 67.
  9. CAO, J., WANG, X., LIN, F., NAKAMURA, H., SINGH, R. Anempirical pHEMT model and its verification in PCS CDMA system.In Proceedings of the 29th European Microwave Conference EuMC,Munich (Germany), 1999, p. 205 - 208.
  10. McCAMANT, A. J., McCORMACK, G. D., SMITH, D. H. An improvedGaAs MESFET model for SPICE. IEEE Transactions on MicrowaveTheory and Techniques, 1990, vol. 38, no. 6, p. 822 - 824.
  11. SMITH, D. H. An improved model for GaAs MESFETs. TechnicalReport. TriQuint Semiconductors Corporation, 2000.
  12. MASSOBRIO, G., ANTOGNETTI, P. Semiconductor device modelingwith SPICE. New York: McGraw-Hill, 1993.
  13. SIJERCIC , E., PEJCINOVIC , B. Comparison of non-linear MESFETmodels. In Proceedings of the 9th International Conferenceon Electronics, Circuits and Systems ICECS, Dubrovnik (Croatia),2002, p. 1187 - 1190.
  14. CHANG, C.-R., STEER, B. R., MARTIN, S., REESE, E. Computeraidedanalysis of free-running microwave oscillators. IEEE Transactionson Microwave Theory and Techniques, 1991, vol. 39, no. 10,p. 1735 - 1744.
  15. WONG, S. C. WinSPICE manual. Version 1.01. Hong Kong: ThePolytechnic University, Dept. of Electronic Engineering, 2000.
  16. PSpice A/D reference guide. Version 10.0. San Jose: Cadence DesignSystems, Inc., 2003.
  17. KLASOVITY, M., HASKO, D., TOMASKA, M., UHEREK, F.Characterization of avalanche photodiode properties in frequency domain.In Proceedings of the 5th Scientific Conference on ElectricalEngineering & Information Technology, Bratislava (Slovakia), 2002,p. 63 - 65.
  18. DOBES, J. Using modified GaAs FET model functions for the accuraterepresentation of PHEMTs and varactors. In Proceedings of the12th IEEE Mediterranean Electrotechnical Conference, Dubrovnik(Croatia), 2004, p. 35 - 38.
  19. ZHANG, Q. J., GUPTA, K. C. Neural networks for RF and microwavedesign. Boston: Artech House, 2000.
  20. XU, J., YAGOUB, M. C. E., DING, R., ZHANG, Q.-J. Neural-baseddynamic modeling of nonlinear microwave circuits. IEEE Transactionson Microwave Theory and Techniques, 2002, vol. 50, no. 12,p. 2769 - 2780.
  21. RAIDA, Z., LUKES , Z., OTEVREL, V. Modeling broadband microwavestructures by artificial neural networks. Radioengineering,2004, vol. 13, no. 2, p. 3 - 11.
  22. DEMUTH, H., BEALE, M. Neural network toolbox for use withMatlab:User's guide. Version 4. Natick: The MathWorks, Inc., 2000.

J. Pospisil, Z. Kolka, S. Hanus, J. Petrzela, J. Brzobohaty [references] [full-text] [Download Citations]
Optimized Second-Order Dynamical Systems and Their RLC Circuit Models with PWL Controlled Sources

Complementary active RLC circuit models with a voltage-controlled voltage source (VCVS) and a current-controlled current source (CCCS) for the second-order autonomous dynamical system realization are proposed. The main advantage of these equivalent circuits is the simple relation between the state model parameters and their corresponding circuit parameters, which leads also to simple design formulas.

  1. POSPISIL, J., KOLKA, Z., HORSKA, J. Synthesis of optimized piecewise-linear system using similarity transformation - part II: second order systems. Radioengineering. 2001, vol. 10, no. 3, p. 8 - 10.
  2. POSPISIL, J., BRZOBOHATY, J. Elementary canonical state models of Chua's circuit family. IEEE Trans. Circ. Syst.-I: Fundamentals. 1996, vol. 43, no. 8, p. 702 - 705.
  3. POSPISIL, J., BRZOBOHATY, J., KOLKA, Z., HORSKA, J. Simplest ODE equivalents of Chua's equations. Intern. Journal of Bifurcation & Chaos. 2000, vol. 10, no. 1, p. 1 - 23.
  4. WU, C. W., CHUA, L. O. On linear topological conjugacy of Lur'e systems. IEEE Trans. Circ. Syst. - I: Fundamentals. 1996, vol. 43, no. 2, p. 158 - 161.
  5. KOLKA, Z. Using similarity transformation for nonlinear system synthesis. In Proc. Radioelektronika' 2001. Brno, 2001, p. 5 - 7.
  6. POSPISIL, J., BRZOBOHATY, J., KOLKA , Z., HORSKA, J., DO-STAL, T. Dynamical systems with low eigenvalue sensitivities. In Proc. MIC'2001, Innsbruck (Austria), 2001, p. 217 - 219.
  7. POSPISIL, J., BRZOBOHATY, J., KOLKA, Z., HANUS, S., DOSTAL, T. Optimized higher-order dynamical systems. In Proc. MIC'2002, Innsbruck (Austria), 2002, vol. I, p. 496 - 499.
  8. HANUS, S. Realization of third-order chaotic systems using their elementary canonical state models. In Proc. Radioelektronika'97, Bratislava (Slovakia), 1997, p. 44 - 45.
  9. POSPISIL, J., BRZOBOHATY, J., KOLKA, Z., HANUS, S., MICHALEK, V. Optimized state model of piecewise-linear dynamical systems. Radioengineering. 2003, vol. 12, no. 1, p. 27 - 29.
  10. MILT, J. Optimization of Dynamical System Eigenvalue Sensitivities Using Its Parameter Modification. (In Czech). Diploma project. Inst. of Radio Electronics, BUT, Brno, 2003.

P. Valtr, P. Pechac [references] [full-text] [Download Citations]
Diffraction Calculations and Measurements in Millimeter Frequency Band

The paper deals with a study of diffraction on dielectric wedge (building corner) in millimeter frequency band, both theoretically and experimentally, to provide knowledge support for ray tracing/launching calculations of MWS interference issues in urban areas. The main motivation was to find balance between reasonably reliable results and necessary demands on calculation complexity and input data accuracy. Verification of Uniform Theory of Diffraction (UTD) was made both for perfectly conducting and dielectric wedge-shaped obstacle. Comparisons of theoretical results and experimental measurement at millimeter waves in anechoic chamber are presented.

  1. ITU-R P.1410 Propagation data and prediction methods required for design of terrestrial broadband millimetric radio access systems operating in a frequency range about 20-50 GHz. ITU-R. 2000.
  2. CLARK, M. P. Wireless access networks. London: John Willey and Sons., 2000.
  3. Report of ACTS Project 215 Cellular Radio Access for Broadband Services (CRABS), "Propagation Planning Procedures for LMDS", 1999.
  4. LEDL, P., PECHAC, P. Area coverage simulations for millimeter point-to-multipoint systems using statistical model of building blockage. Radioengineering. 2002, vol. 11, no. 4, p. 43-47.
  5. KLEPAL, M., HRADECKY, Z., MAZANEK, M., PECHAC, P. Theory and modelling of electromagnetic wave propagation and design leading to reduction of information leakage due to electromagnetic radiation. [Research Report]. Prague, CTU, Faculty of Electrical Engineering, Department of Electromagnetic Field, 2002. K317/1/VZ/02. 53 p. (in Czech).
  6. KOUYOUMJIAN, R. G., PATHAK, P. H. A uniform geometrical theory of diffraction for an edge in a perfectly conducting surface. Proc. IEEE. 1974, vol. 62, p. 1448-1461.
  7. KELLER, J. B. Geometrical theory of diffraction. J. Opt. Soc. of America. 1962, vol. 52, no. 2, p. 116-130.
  8. LUEBBERS, R. J. Finite conductivity uniform GTD versus knife edge diffraction in prediction of propagation path loss. IEEE Transactions on Antennas and Propagation. 1984, vol. AP-32, no. 1, p. 70-76.

T. Hult, A. Mohammed [references] [full-text] [Download Citations]
Suppression of EM Fields using Active Control Algorithms and MIMO Antenna System

Active methods for attenuating acoustic pressure fields have been successfully used in many applications. In this paper we investigate some of these active control methods in combination with a MIMO antenna system in order to assess their validity and performance when applied to electromagnetic fields. The application that we evaluated in this paper is a model of a mobile phone equipped with one ordinary transmitting antenna and two actuator-antennas which purpose is to reduce the electromagnetic field at a specific area in space (e.g. at the human head). Simulation results show the promise of using the adaptive active control algorithms and MIMO system to attenuate the electromagnetic field power density.

  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. GABRIEL, C. Compilation of the Dielectric Properties of Body Tissues at RF and Microwave Frequencies. Brooks Air Force Tech-nical Report AL/OE-TR-1996-0037.
  5. HULT, T. Active Suppression of Electromagnetic Fields. Master Thesis, Blekinge Institute of Technology, 2002. [dB]
  6. HULT, T.; MOHAMMED, A.; NORDEBO, S. Active Suppression of Electromagnetic Fields using a MIMO Antenna System. In 17th Int. Conf. on Appl. Electromagnetics and Commun. ICECom 2003, 2003.

P. Hanzlik, P. Pata [references] [full-text] [Download Citations]
Behind the Structure of Video VQ-Coder

This paper introduces an implementation and structure of a video codec (coder-decoder) using Vector Quantization (VQ) in the program Matlab. It also aims on the VQ weak and strong features and it describes an experiment with turning the advantages into concrete profit in video data compression. We would like to aim also on usage in video MPEG 4 (Motion Picture Experts Group) standard or in compressing the scientific (high resolution) images. In conclusion we are comparing our approach with other image compression methods with objective and subjective criteria of image quality perception.

  1. GERSHO, A., GRAY, R. M. VQ and signal compression. Kluwer Academic Publishers, 1992.
  2. ABUT, H. Vector Quantization. Piscataway: IEEE Press, 1990.
  3. KLIMA, M., BERNAS, M., HOZMAN, J., DVORAK, P. Zpra-covani obrazove informace. Praha: CVUT, 1996 (in Czech).
  4. VIT, V. et al. Televizni technika. Praha: SNTL, 1979 (in Czech).
  5. KOSTAL, E. Obrazova a televizni technika II. - Televize. Praha: CVUT, 1998 (in Czech).
  6. Encyclopedia of Computing Science and Technology 29. New York: M. Dekker, [1975- present] (supplement 14).
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  8. ITU-T Methods for the Subjective Assessment of the Quality of Television Pictures. ITU-T Recommendation 500-2, 1982.
  9. ITU-T Subjective Video Quality Assessment Methods for Multimedia Applications. ITU-T Recommendation P 910, August1996.
  10. ITU-T Video Coding for Low Bitrate Communication. ITU-T Recommendation H.263; version 1, Nov. 1995; version 2, Jan. 1998.

V. Sadek, J. Svacina [references] [full-text] [Download Citations]
Analysis of Homogeneous Coplanar Strip Line

The goal of this work is to introduce a new, maybe complicated but in the final result mathematically simplest model of the coplanar strip line (CPS). In contrast to the usual method based on elliptical integrals the simplest circular inversion is applied. The main advantage is that our solution is mathematically less complicated but its accuracy is a little bit lower. The maximal error of the model described lies within the restricted interval between -3% and 3%. Nevertheless the final formula is useful for the practical engineering application.

  1. NAVRATIL V., LEONE M. The effect of differential driver asymmetries on common- and differential-mode frequency spectrum with regard to EMC. In Proc. of the 4th International Conference of Ph.D. Students. Miskolc (Hungary), 2003.
  2. HOFFMAN, K. Planarni mikrovlnne obvody (Planar microwave circuits). The textbook of the Czech Technical University of Prague, Praha, 2001 (in Czech).
  3. WADELL, B.C. Transmission line design handbook. Boston/ Lon-don: Artech House, 1991.
  4. SADEK, V., DYMAL, P., PROKOPEC, J., SVACINA, J. Mapping of the coplanar strips and coplanar waveguide to the cylindrical segments. In Elektrotechnika a informatika 2003. Plzen, 2003, p. 128 to 130.
  5. SADEK V., RAIDA Z., SVACINA J. Analysis of the cylindrical segments. In Proc. of Radioelektronika 2004. Bratislava (Slovakia), 2004, p. 209 - 212.
  6. HENRICI, P. Applied and computational complex analysis I. and III. Wiley Classic Library, New York/London/Sydney/Toronto, 1988.
  7. DRISCOLL, T. A., TREFETHEN, L. N. Schwarz-Christoffel map-ping. Cambridge Monographs on Applied and Computational Mathematics. Cambridge University Press, 2002.
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  9. HLAVKA, J., KLATIL, J., KUBIK, S. Komplexni promenna v elektrotechnice (Complex variable in electrical engineering). Praha: SNTL, 1990 (in Czech).
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M. Jelinek, J. Dobes, L. Pousek [references] [full-text] [Download Citations]
Correlation Analysis in a Pulse Wave Velocity Evaluation

In this paper, methods for a time delay evaluation of phonocardiographic (PCG) signals are presented to estimate a pulse wave velocity (PWV) in a cardiovascular system of a human body, especially in arterial segments of an arterial tree selected. A measuring method used for the pulse wave registration is fully non-invasive. Electronic phonendoscopes pressure/acoustic converters were used as signal transducers. The PWV estimation was carried out using correlation analysis of PCG signals, square of raw PCG signals and the first derivations of PCG signals. Signal processing, i.e. filtration, standardization, etc. was implemented in a Matlab environment using created application. A set of subjects examined in this experiment consists of five young healthy volunteers.

  1. VALENTA, J. et al. Biomechanics. 1st ed. Prague: Academia, 1993.
  2. OLIVA, I., ROZTOCIL, K. The pulse wave in diagnosis of occlusive arterial disease (In Czech: Pulsova vlna v diagnostice ischemicke choroby dolnich koncetin). Prague: Avicenum, 1982.
  3. ASMAR, R. Arterial stiffness and pulse wave velocity - Clinical applications. Paris: Elsevier, 1999.
  4. SILBERNAGL, S., DESPOPOULOS, A. Atlas of human body physiology (In Czech: Atlas fyziologie cloveka). Prague: Avicenum, 1993.
  5. AKAY, M. Biomedical signal processing. San Diego: Academic Press, 1994.
  6. HRDINA, Z., VEJRAZKA, F. Signals and systems (In Czech: Signaly a soustavy). Prague: CTU Press, 2001.
  7. JELINEK, M., DOBES, J., POUSEK, L., HANA, K. Using a phonocardiography in a pulse wave velocity measurement. In Proceedings of the IEEE International Symposium on Signal Processing and Information Technology. Darmstadt (Germany), 2003, p. 5/TP3.
  8. PENHAKER, M. The new aspects on systematic diagnostics of plethysmographycal record. In Proceedings of the 2nd European Medical and Biological Engineering Conference. Vienna (Austria), 2002, p. 414 - 415.
  9. KURODA, T., HAYASHI, Y., NISHIDA, M., ZHANG, D., HIRAO, Y. The method of the blood flow measurement during exercise by using the linear array type ultrasonic probe. In Proceedings of the 2nd European Medical and Biological Engineering Conference. Vienna (Austria), 2002, p. 516 - 517.
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  12. WEBSTER, J. Medical instrumentation - Application and design. Dallas: Houghton Mifflin, 1992.

P. Cerva, J. Nouza [references] [full-text] [Download Citations]
MAP Based Speaker Adaptation in Very Large Vocabulary Speech Recognition of Czech

The paper deals with the problem of efficient adaptation of speech recognition systems to individual users. The goal is to achieve better performance in specific applications where one known speaker is expected. In our approach we adopt the MAP (Maximum A Posteriori) method for this purpose. The MAP based formulae for the adaptation of the HMM (Hidden Markov Model) parameters are described. Several alternative versions of this method have been implemented and experimentally verified in two areas, first in the isolated-word recognition (IWR) task and later also in the large vocabulary continuous speech recognition (LVCSR) system, both developed for the Czech language. The results show that the word error rate (WER) can be reduced by more than 20% for a speaker who provides tens of words (in case of IWR) or tens of sentences (in case of LVCSR) for the adaptation. Recently, we have used the described methods in the design of two practical applications: voice dictation to a PC and automatic transcription of radio and TV news.

  1. GAUVAIN, J.L., LEE, C.H. Maximum a posteriori estimation for multivariate Gaussian mixture observations of Markov chains. IEEE Trans. SAP. 1994, vol. 2, p. 291 - 298.
  2. HUANG, X.D., ACERO, A., HON, H.W. Spoken language proces-sing. Englewood Cliffs: Prentice Hall, 2001.
  3. CERVA, P. Methods of speaker adaptation for speech recognition system. Diploma thesis (in Czech). TU of Liberec. 2004.
  4. NOUZA, J., PSUTKA, J., UHLIR, J. Phonetic alphabet for speech recognition of Czech. Radioengineering. 1997, vol. 6, no. 4, p.16 to 20.
  5. NOUZA, J., NOUZA, T. A Voice dictation system for a million-word Czech vocabulary. Proc. of Conference on Computing, Com-munication and Control Technologies. Austin, 2004.
  6. NOUZA, J., NEJEDLOVA, D., ZDANSKY, J., KOLORENC, J. Very large vocabulary speech recognition system for automatic trans-cription of Czech broadcast programs. Proc. of Int. Conference on Spoken Language Processing (ISCLP'04). Jeju, 2004.
  7. ZELEZNY, M. Speaker adaptation in continuous speech recognition system of Czech. PhD thesis (in Czech). ZCU Plzen 2001.

L. Longauer, S. Marchevsky, D. Kocur [references] [full-text] [Download Citations]
BAMUD Features Demonstration by System View

Direct-sequence code-division multiple access (DS-CDMA) is a frequently used wireless technology in DS-CDMA communications. The conventional DS-CDMA detector follows a single-user detection strategy in which each user is detected separately without regard for the other users. The better strategy is multi-user detection (MUD), where information about multiple users is used to improve detection of each individual user. This paper presents an adaptive multi-user detector converging (for any initialization) to the minimum mean square error (MMSE) detector without requiring training sequences. This blind multi-user detector (BAMUD) requires no more knowledge than does the conventional single-user detector. The structure of adaptive blind detector is simulated by the system design tool SystemView. The aim focus is to verify theoretical knowledge of BAMUD structure using hardware-oriented PC-based model in SystemView.

  1. GLISIC, S., VUCETIC, B. Spread spectrum CDMA systems for wireless communication. Norwood: Artech House, 1997.
  2. LASTER, J. D., REED, J. R. An overview of the advanced adaptive filtering technique. IEEE Signal Process. Magazine, 1997, p. 36-62.
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  4. VERDU, S. Multi-user detection. Cambridge Univ. Press, UK, 1998.
  5. HONIG, M., MADHOW, U., VERDU, S. Blind adaptive multi-user detection. IEEE Transaction on Information Theory, 1995, vol. 41, no. 4, p. 944 - 960.
  6. HONIG, M., TSATSANIS, M. K. Adaptive techniques for multi-user CDMA receivers. IEEE Signal Processing Magazine, May 2000, vol. 17, no. 9, p. 49 - 61.
  7. MOSHAVI, S. Multi-user detection for DS - CDMA communications. IEEE Communications Magazine, October 1996, vol. 34, no. 10, p. 124 - 136.
  8. XUE, G., WENG, J., LE-NGOC-TAHAR S. T. Multi-user detection techniques: An overview. Technical Report. Dept. of Electrical and Computer Engineering, Concordia University, Canada, 1998.
  9. DEL RE, E. Trends on Satellite Communications. Presentation, Scuola di Dottorato, Napoli (Italy), February 2003.
  10. MUCCHI, L., RONGA, L. S., DEL RE, E. Two-State CDMA Receiver for Shared Uplink Satellite Channel. European Mo-bile/Personal Satcoms Conference, Baveno / Stresa - Lake Maggiore (Italy), Sept. 25 - 26, 2002.
  11. AVUDAINAYGAM, A. Linear and Adaptive Linear Multiuser Detection in CDMA systems. Course project, EEL 6503:Spread Spectrum and CDMA course project,
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  14. KOCUR, D., CIZOVA, J. Multi-user detection techniques for CDMA: A review of basic principles. In Proc. Acta Electronica et Informatica, Kosice, Slovakia, vol. 3, no.1, p. 28 - 35.
  15. WIESER, V., CHMURNY, J. Microcell DS-CDMA System Capacity Maximalization. In Proc. of Army Academy, Liptovsky Mi-kulas, 1998, no. 1, p. 41- 49 (in Slovak).
  16. WIESER, V. Transmitter Adaptive Power Control in Channel with Willful Interference. In Proc. of the Scientific Conf. Trends in fyrd technics. Army Academy, Lipt Mikulas, 1998, p.110-115 (in Slovak)