Publications

Impact Journal Papers

[1] Ivo Bukovsky, Noriyasu Homma, Kei Ichiji, et al., “A Fast Neural Network Approach to Predict Lung Tumor Motion during Respiration for Radiation Therapy Applications,” BioMed Research International, Article ID 489679, in press.

[2] Bukovsky, I.: ¨Learning Entropy: Multiscale Measure for Incremental Learning¨, journal of Entropy, special issue on Dynamical Systems,, ISSN 1099–4300, 2013, 15(10), 4159-4187; doi:10.3390/e15104159.

[3] Bila, J., Jura, J., Pokorny, J., Bukovsky, I.: “Qualitative Modeling and Monitoring of Selected Ecosystem Functions”, in Ecological Modelling, Volume 222, Issue 19, 10 October 2011, Elsevier, ISSN: 0304-3800, pp. 3640-3650.

Book Chapters

[4] Gupta, M., M., Bukovsky, I., Homma, N. , Solo M. G. A., Hou Z.-G.: “Fundamentals of Higher Order Neural Networks for Modeling and Simulation“, in Artificial Higher Order Neural Networks for Modeling and Simulation, ed. M. Zhang, IGI Global, 2012.

[5] Bukovsky, I., Bila. J: “Adaptive Evaluation of Complex Dynamic Systems using Low-Dimensional Neural Architectures”, Springer's book on Advances in Cognitive Informatics and Cognitive Computing, Series: Studies in Computational Intelligence, Vol. 323, eds. D. Zhang, Y. Wang, W. Kinsner, ISBN: 978-3-642-16082-0, pp.282, November 2010

[6] Bukovsky, I., Bila, J., Gupta, M., M, Hou, Z-G., Homma, N.: “Foundation and Classification of Nonconventional Neural Units and Paradigm of Nonsynaptic Neural Interaction” in Discoveries and Breakthroughs in Cognitive Informatics and Natural Intelligence series  Advances in Cognitive Informatics and Natural Intelligence (ACINI), ed. Y. Wang,  IGI Publishing, Hershey PA, USA,  Nov.. 2010. ISBN: 978-1-60566-902-1, pp.508-523

[7] Gupta, M., M, Homma, N., Hou, Z-G., Solo, M., G., Bukovsky, I.: “Higher Order Neural Networks: Fundamental Theory and Applications”, in Artificial Higher Order Neural Networks for Computer Science and Engineering: Trends for Emerging Applications", ed. M. Zhang, IGI Global, 2010,  ISBN 13: 978-1-61520-711-4, pp.397-422.

International Reviewed Journal Papers

[8] A. Vagaská, P. Michal, I. Bukovský, M. Gombár and J. Kmec: "Mathematical Modelling and Description of the Technological Process of Aluminum Anodic Oxidation by Using the Neural Networks", International Journal of Materials, NAUN, Volume 1, 2014.

[9] Bukovsky, I., Kolovratnik M.: „A Neural Network Model for Predicting NOx at the Mělník 1 Coal-powder Power Plant“, Acta Polytechnica ,Vol. 52 No. 3/2012,pp.17-22, ISSN 1805-2363, 2012.

[10] Rodriguez , R., Bukovsky, I., Homma, N.: “Potentials of Quadratic Neural Unit for Applications”, in International Journal of Software Science and Computational Intelligence (IJSSCI) ,vol 3, issue 3, IGI Global, Publishing, Hershey PA, USA ISSN 1942-9045, DOI: 10.4018/jssci.2011070101 July-September 2011, pp.1-12.

[11] Homma, N., Kato, S., Goto, T., Bukovsky, I., Kawashima, R., and Yoshizawa, M.: “How Can Brain Learn to Control a Nonholonomic System?”, in special issue of Journal of Robotics on Volume 2010 (2010), Article ID 919306, 7 pages.

[12] Bukovsky, I., Hou, Z-G., Bila, J., Gupta, M., M.: “Foundation of Nonconventional Neural Units and their Classification”, International Journal of Cognitive Informatics and Natural Intelligence (IJCiNi), 2(4), October-December 2008, IGI Publishing, Hershey PA, USA, pp.29-43, ISSN 1557-3958.

Local Journal Papers

[13] Bukovsky, I., Rodriguez, R., Bila, J., “Prospects of Gradient Methods for Nonlinear Control”, Strojárstvo Extra, MEDIA/ST, s.r.o. publishing house, 2012, ISSN 1335-2938.

[14] Bukovsky, I., Homma, N.: “Dynamic Backpropagation and Prediction (Dynamický backpropagation a predikce)” (in Czech), In: Automatizace, Vol. 53, No. 1-2, Prague, Czech Republic, Jan-Feb 2010, p.61-66, ISSN 0005-125X.

[15] Bukovsky,  I., Homma, N.: “Dynamic Backpropagation (Dynamický backpropagation)”  (in Czech),  In: Automatizace, Vol. 52, No. 10, Prague, Czech Republic, Oct 2009, p.586-590, ISSN 0005-125X.

[16] Bukovsky, I., Bila, J., Gupta, M., M.: “Linear Dynamic Neural Units with Time Delay for Identification and Control" (in Czech), In: Automatizace, Vol. 48, No. 10, Prague, Czech Republic, Oct 2005, p. 628-635. ISSN 0005-125X.

[17] Bíla, J., Vitkaj, J., Musil, M., Bukovsky, I.: “Some Limits of Neural Networks Use in Diagnostics” (in Czech),In.:  Automatizace, vol. 46, issue 11,  2003, Prague, ISSN 0005 -125X, pp.734-737.

Conference Papers

[18] Ivo Bukovsky, Cyril Oswald, Matous Cejnek, Peter M. Benes:" Learning Entropy for Novelty Detection A Cognitive Approach for Adaptive Filters", accepted paper for Sensor Signal Processing for Defence (SSPD) Conference 2014, Edinburgh, UK, Sept. 8-9, 2014

[19] Ivo Bukovsky, Noriyasu Homma, Matous Cejnek and Kei Ichiji: "Study of Learning Entropy for Novelty Detection in Lung Tumor Motion Prediction for Target Tracking Radiation Therapy", The 2014 International Joint Conference on Neural Networks (IJCNN 2014), IEEE WCCI 2014, Beijing, 2014.

[20] Peter Benes and Ivo Bukovsky: "Neural Network Approach to Hoist Deceleration Control", The 2014 International Joint Conference on Neural Networks (IJCNN 2014), IEEE WCCI 2014, Beijing, 2014.

[21] Peter Michal, Jan Pitel, Alena Vagaska and Ivo Bukovsky: "Application of Neural Networks to Evaluate Experimental Data of Galvanic Zincing", The 2014 International Joint Conference on Neural Networks (IJCNN 2014), IEEE WCCI 2014, Beijing, 2014.

[22] Peter Mark Benes, Ivo Bukovsky, Matous Cejnek, Jan Kalivoda: "Neural Network Approach to Railway Stand Lateral Skew Control" in Computer Science & Information Technology (CS& IT), Sydney, NSW, Australia, AIRCC, 2014, pp. 327-339. DOI:10.5121/csit.2014.4228

[23] Matous Cejnek, Peter Mark Benes, Ivo Bukovsky: "Another Adaptive Approach to Novelty Detection in Time Series", in Computer Science & Information Technology (CS& IT), Sydney, NSW, Australia, AIRCC, 2014, pp. 341-351. DOI:10.5121/csit.2014.4229

[24] Alena Vagaská, Peter Michal, Miroslav Gombár, Ján Kmec: "The Application of Neural Networks to Control Technological Process", Proceedings of the 2013 International Conference on Applied Mathematics and Computational Methods, Europment, 2013, Italy.

[25] Bukovsky, I., Kinsner, W., Bila, J.: „Multiscale Analysis Approach for Novelty Detection in Adaptation Plot“,3^rd Sensor Signal Processing for Defence 2012 (SSPD 2012), Imperial College London, UK, September 24-27, 2012.

[26] Witold Kinsner, Simon Haykin, Yingxu Wang, Witold Pedrycz, Ivo Bukovsky, Bernard Widrow, Andrzej Skowron, Piotr Wasilewski, and Menahem Friedman: “Challenges in Engineering Education of Cognitive Dynamic Systems”, Proceedings of the Canadian Engineering Education Association 2012 (conf. CEEA12).

[27] Bukovsky, I., Kolovratnik, M.: “Neural Network Model for Prediction of NOx at Coal-Powder Powerplant Mělník 1”, ERIN 2012, CTU in Prague, 25–27 April 2012, Czech Rep.

[28] Bukovsky, I., Kinsner, W., Bila, J.: “Multiscale Approach to Uncertainty Evaluation of Input-Output Data” Automatizácia a riadenie v teórii a praxi ARTEP 2012, Slovakia 2012, ISBN: 978-80-553-0835-7.

[29] Bukovsky, I., Kinsner, W., Maly, V., Krehlik, K.: “Multiscale Analysis of False Neighbors for State Space Reconstruction of Complicated Systems”, in proceedings of 2011 IEEE Symposium Series on Computational Inteligence (SSCI), IEEE Workshop CompSens 2011: ISBN 978-1-4577-0470-3, Paris 2011, pp. 35-41.

[30] Ichiji, K., Homma, N., Bukovsky, I., Yoshizawa, M..: “Intelligent Sensing of Biomedical Signals - Lung Tumor Motion Prediction for Accurate Radiotherapy”, in proceedings of 2011 IEEE Symposium Series on Computational inteligence (SSCI), IEEE Workshop CompSens 2011: ISBN 978-1-4577-0470-3, Paris 2011, pp. 65-72.

[31] Bila, J., Bukovsky, I.,: “Modeling and Interpretation of New Solutions in Problem Solving”, 2011 12th International Carpathian Control Conference (ICCC), DOI: 10.1109/CarpathianCC.2011.5945808,  25-28, May 2011, Czech Republic.

[32] Bila, J., Jura, J., Bukovsky, I., 2011. “Qualitative modeling in the landscape development monitoring“, in: 15th Int. WSEAS Conf. on Systems—CSCC 2011, Corfu, Greece, pp.35–41.

[1] Bukovsky, I., Lepold, M., Bila J.: “Quadratic Neural Unit and its Network in Validation of Process Data of Steam Turbine Loop and Energetic Boiler”,WCCI 2010,  IEEE Int. Joint. Conf. on Neural Networks IJCNN, Barcelona, Spain, 2010.

[2] Bukovsky, I., Ichiji, K., Homma, N., Yoshizawa, M.: “Testing Potentials of Dynamic Quadratic Neural Unit for Prediction of Lung Motion during Respiration for Tracking Radiation Therapy”, WCCI 2010, IEEE Int. Joint. Conf. on Neural Networks IJCNN, Barcelona, Spain, 2010.

[3] Bukovsky, I., Homma, N.,  Smetana, L., Rodriguez, R., Mironovova M., Vrana S.,: “Quadratic Neural Unit is a Good Compromise between Linear Models and Neural Networks for Industrial Applications”, ICCI 2010 The 9th IEEE International Conference on Cognitive Informatics, Tsinghua University, Beijing, China, July 7-9, 2010.

[4] Rodriguez R., Ichiji K., Bukovsky I., Bila J., Homma N.: “Lung Motion Prediction by Static Neural Networks“, 4th International Symposium on Measurement, Analysis and Modelling of Human Functions,IMEKO, Prague, 2010

[5] Bila, J., Bukovsky, I., Jura. J.: “Review of Development of Nonconventional Neural Architectures at the Czech Technical University in Prague“, 10th WSEAS Int. Conf. on NEURAL NETWORKS (NN'09), pp.138-146, Prague, Czech Republic, 2009. ISSN: 1790-5109, ISBN: 978-960-474-065-9 (Best conference paper).

[6] Bila,  J.,  Jura.  J.,  Bukovsky,  I.:  “Qualitative  Modeling  and  Monitoring  of  the  Selected  Ecosystem Violated  with  Parasitic  Dehumidifying  and  Dehydrating“,  WSEAS  International  Conference  on Automation and Information (ICAI'09), Prague, Czech Republic, 2009.

[7] Bukovsky, I., Anderle, F., Smetana, L.,: “Quadratic Neural Unit for Adaptive Prediction of Transitions among Local Attractors of Lorenz System”, 2008 IEEE International Conference on Automation and Logistics, Qingdao, China, 2008, ISBN  978-1-4244-2503-7.

[8] Bukovsky, I, Bila, J.: „Adaptive Evaluation of Complex Time Series using Nonconventional Neural Units“, ICCI 2008,  The 7th IEEE International Conference on COGNITIVE INFORMATICS, California , USA, 2008, ISBN 9781424425389.

[9] Bukovsky, I., Smetana, L., Anderle, F.: “Adaptive Prediction of Transitions between Local Attractors of Lorenz’s System“. (in Czech), In: New Methods and Approaches in the Fields of Control Technology, Automatic Control, and Informatics, Czech Technical University, Prague, U12110.3, Czech Republic, 2008.

[10] Simeunovic , G., Bukovsky, I.: The Implementation of the Dynamic-Order-Extended Time-Delay Dynamic Neural Units to Heat Transfer System Modelling, 16th International Conference on Nuclear Engineering (ICONE 16), Orlando, Florida, USA, May 11-15, 2008, ISBN 0-7918-3820-X.

[11] Bukovsky, I., Hou, Z-G., Gupta, M., M., Bila, J.: “Foundation of Notation and Classification of Nonconventional Static and Dynamic Neural Units”, accepted paper for special section on neural networks for ICCI 2007,  The 6th IEEE International Conference on COGNITIVE INFORMATICS, California , USA, 2007, ISBN: 978-1-4244-1328-7.

[12] Bukovsky, I., Bila, J.: „Basic Classification of Nonconventional Artificial Neural Units”(In Czech), Proceedings of Seminar Nove Hrady, Czech Technical University in Prague, FME, ISBN: 978-80-01-03747-8, Czech Republic, 2007, pp. 76-80.

[13] Bukovsky, I., Simeunovic, G.: Dynamic-Order-Extended Time-Delay Dynamic Neural Units, Accepted paper for 8th Seminar on Neural Network Applications in Electrical Engineering, NEUREL-2006, IEEE (SCG) CAS-SP, Belgrade, 2006

[14] Bukovsky, I., Bíla, J., Gupta, M., M.: Stable Neural Architecture of Dynamic Neural Units with Adaptive Time Delays 7th International FLINS Conference on Applied Artificial Intelligence, 2006, p. 215-222, ISBN 981-256-690-2

[15] Bila, J., Brandejsky, T., Bukovsky, I.: A Non-traditional Software Support Conceptual Design System - CD3., 5th International Conference on Advanced Engineering Design 2006, , Czech Technical University, Czech Republic, Prague, 2006

[16] Bukovsky, I.: Extended Dynamic Neural Architectures HONNU with Minimum Number of Neural Parameters for Evaluation of Nonlinear Dynamic Systems (in Czech), In: New Methods and Approaches in the Fields of Control Technology, Automatic Control, and Informatics, Czech Technical University, Prague, 2005, s. 93-97. ISBN 80-01-03240-X.

[17] Bukovský, I. – Bíla, J.: Nelineární dynamické neuronové jednotky pro paralelní manipulátor TRIPOD. In: Sborník ze semináře VZ MSM 212200008 [CD-ROM]. Praha: ČVUT, Fakulta strojní, 2004, díl 1, s. 66–68. ISBN 80-01-03105-5.

[18] Bukovsky I., Bila J. : Development of Higher Order Nonlinear Neural Units for Evaluation of Complex Static and Dynamic Systems, Proceedings of Workshop 2004, Part A, March 2004, Vol.8, Special Issue, Czech Technical University, Czech Republic, Prague, pp. 372-373, ISBN 80-01-02945-X

[19] Bila, J., Brandejsky, T., Jelinek, I., ith - Bukovsky, I. Software Support of Conceptual Design Process In: Workshop 2004 [CD-ROM]. Prague: Czech Technical University in, Czech Republic, Prague 2004, vol. A, s. 378-379. ISBN 80-01-02945-X

[20] Bukovsky I., S. Redlapalli and M. M. Gupta : Quadratic and Cubic Neural Units for Identification and Fast State Feedback Control of Unknown Non-Linear Dynamic  Systems, Fourth International Symposium on Uncertainty Modeling and Analysis ISUMA 2003, IEEE Computer Society, 2003, Maryland USA, ISBN 0-7695-1997-0, p.p.330-334

[21] Bila J., Bukovsky I., Oliviera T., Martins J, I. :  Modeling Of Influence Of Autonomic Neural System To Heart Rate Variability, IASTED International Conference On Artificial Intelligence And Soft Computing ~Asc 2003~, ACTA Press, 2003, Banff, Canada, Pp.345-350

[22] Bila, J., Bukovsky, I. : Modelling and Interpretation of Chaotic Phenomena in Heart Rate. In: Proceedings of 8^th International  Conference on Soft Computing, MENDEL 2002, Brno, Czech Republic,2002 , ISBN 80-214-2135-5, pp.292-297

[23] Bila, J., Bukovsky, I. : Interpretation of Chaotic Phenomena in Heart Rate. In: Proceedings of Workshop 2002, Part B, February 2002, Vol.6, Special Issue, Czech Technical University, Czech Republic, Prague, ISBN 80-01-02511-X, pp. 908-909

[24] Bíla, J., Zítek, P., Kuchař, P. and Bukovsky, I.: Heart Rate Variability: Modelling and Discussion. In: Proc. of Int. IASTED Conf. - NN 2000, Pittsburgh, USA, 2000, pp. 54-59. ISBN-0-88986-286-9.

Editorial Papers

[25] Madan M. Gupta, Ivo Bukovsky, Noriyasu Homma, Zeng-Guang Hou, and Ashu, M. G. Solo: “Cognitive and Neural Aspects in Robotics 2011”, in Cognitive and Neural Aspects in Robotics 2011, as annual issue of Journal of Robotics, Volume 2012 (to appear in 2012).

[26] Baglietto, M., Benuskova, L. L., Bukovsky, I., Chen, T., Heskes, T., Ikeda, K., Karray, F., Kil, R. M., Legenstein, R., Lu, J., Ma, Y., Magdon-Ismail, M., Paulin, M., Polikar, R., Prokhorov, D., Wiering, M., Zarzoso, V.: “Editorial: One Year as EiC, and Editorial-Board Changes at TNN”, in IEEE Transactions on Neural Networks, Volume: 22 Issue:1 , ISSN: 1045-9227, 2011.

[27] Madan M. Gupta, Noriyasu Homma, Zeng-Guang Hou, and Ivo Bukovsky: “Cognitive and Neural Aspects in Robotics with Applications”, in special issue of Journal of Robotics on Cognitive and Neural Aspects in Robotics with Applications, Volume 2010 (2010).

Research Project Reports

[28] Bukovský, I.: Křehlík, K.: Testy neuronového modelu kotle elektrárny Mělník I, research report (Výzkumná zpráva č. 8-ZI00069/ E06) for I. & C. Energo, a.s. U12110, Faculty of Mechanical Engineering, Czech Technical University in Prague, 2011, 61 pages

[29] Bukovský, I.: Křehlík, K.: Otestování metody extrapolace pyrometrických měření na základě neuronových sítí, research report # 7-ZI00069/E05 for I. & C. Energo, a.s., U12110, Faculty of Mechanical Engineering, Czech Technical University in Prague, 2011, 16 pages

[30] Bukovsky, I.: Návrh regulačního algoritmu kotle na základě neuronového modelu elektrárny Mělník I, research report (Výzkumná zpráva č. 8-ZI00069/ E02) for I. & C. Energo, a.s. U12110, Faculty of Mechanical Engineering, Czech Technical University in Prague, 2011, 6 pages

[31] Bukovsky, I..: Dynamické neuronové sítě pro nestacionární modely a validaci veličin energetických procesů (Dynamical Neural Networks for Nostationary Models and for Validation of Variables of Energetic Processes), Výzkumná zpráva č. 4 pro I. & C. Energo, a.s. U12110, Faculty of Mechanical Engineering, Czech Technical University in Prague, 2010, 40 pages.

[32] Bukovsky, I.: Návrh metodiky extrapolace obrazců řezu spalovací komorou (Development of Extrapolation Method for Thermal Images in Combustion Chamber), Výzkumná zpráva č. 5 pro I. & C. Energo, a.s. U12110, Faculty of Mechanical Engineering, Czech Technical University in Prague, 2010, 6 pages.

[33] Bukovsky, I.; Nonconventional neural networks and validation of process data, research report for I. & C. Energo, a.s. U12110, Faculty of Mechanical Engineering, Czech Technical University in Prague, 2009, 93 pages.

[34] Bukovsky, I., Bila. J: Program system for advanced reconciliation of process data: Program System I&C NEURECON (In Czech, Programový systém pro pokročilé validování provozních dat: Programový systém I&C NEURECON), Final report for I. & C. Energo, a.s. U12110, Faculty of Mechanical Engineering, Czech Technical University in Prague, 2008, 107 pages.

[35] Bukovsky, I., Bila. J: Analysis of Methods for Evaluation of Data Uncertainty for Control of Energetic Systems (In Czech, Analýza metod pro stanovování neurčitostí dat pro řízení provozu energetických zařízení), report for I&C Energo, a.s. U12110, Faculty of Mechanical Engineering, Czech Technical University in Prague, 2007, 128 pages.

[36] Bukovsky, I. : Development of Higher-Order Nonlinear Neural Units as a Tool for Approximation, Identification and Control of Complex Nonlinear Dynamic Systems and Study of Their Application Prospects for Nonlinear Dynamics of Cardiovascular System, Final report from scientific research under NATO Science Fellowships at the Intelligent System Research Laboratory at the University of Saskatchewan in Canada from April to October 2003 partially supported by Internal Grant of Czech Technical University (IGS #CTU0304112 ), 2003, 32 pages.

Tutorial

[37] Ivo Bukovsky, Jiri Bila, Madan M. Gupta, and Zeng-Guang Hou: NEW NEURAL ARCHITECTURES AND NEW ADAPTIVE EVALUATION OF CHAOTIC TIME SERIES, TUTORIAL for 2008 IEEE International Conference on AUTOMATION AND LOGISTICS, August 31 2008, 2:00pm – 5:00pm, Qingdao, China, 2008.

(Download pdf from IEEE CIS Multimedia Tutorials Center)

Invited Speeches

[38] NEW NEURAL ARCHITECTURES AND NEW ADAPTIVE EVALUATION OF CHAOTIC TIME SERIES, key-note presentation for 15th International Research/Expert Conference ”Trends in the Development of Machinery and Associated Technology TMT2011, September 2011, Prague.

[39] NONCONVENTIONAL NEURAL ARCHITECTURES ADAPTIVE METHODOLOGY AND MULTI-SCALE ANALYSIS: CHALLENGES FOR BIOMEDICAL ENGINEERING APPLICATIONS, lecture at the Yoshizawa-Homma Lab, Research  Division  on  Advanced  Information  Technology, Graduate  School of  Engineering, Tohoku  University, 15:00-16:30, July 23, 2011, Sendai, Japan. 

[40] QUADRATIC NEURAL UNIT & QUADRATIC NEURAL NETWORK: A COMPROMISE FOR INDUSTRIAL APPLICATIONS, IEEE Seminar, Fort Garry Campus, EITC Rm. E2-393,  2:30 - 3:30 PM, Tuesday, June 29, 2010,  organizers: IEEE Computer & Computational Intelligence Chapter, Department of Electrical and Computer Engineering (Prof. Witold Kinsner), Department of Mechanical and Manufacturing Engineering, Institute of Industrial Mathematical Sciences, University of Manitoba, Canada.

[41] ADAPTIVE METHODOLOGY FOR MONITORING AND EVALUATION OF DYNAMICAL SYSTEMS, IEEE Seminar, Fort Garry Campus, EITC Rm. E2-393,  2:30 - 3:30 PM, Monday, June 21, 2010,  organizers: IEEE Computer & Computational Intelligence Chapter, Department of Electrical and Computer Engineering (Prof. Witold Kinsner), Department of Mechanical and Manufacturing Engineering, Institute of Industrial Mathematical Sciences, University of Manitoba, Canada.

[42] NONCONVENTIONAL NEURAL ARCHITECTURES AND APPLICATIONS FOR COMPLEX SYSTEMS,  lecture at Research  Division  on  Advanced  Information  Technology (Dr. Noriyasu Homma), Graduate  School  of  Engineering, Tohoku  University,  15:00-16:30, July 14, 2009, Sendai,  Japan. 

[43] NEW NEURAL ARCHITECTURES AND NEW ADAPTIVE EVALUATION OF CHAOTIC TIME SERIES in Lecture Series in Complex Systems and Intelligence Science, Institute of Automation, The Chinese Academy of Sciences, Beijing, China, 10:00–11:30am, September 8, 2008. (organized by Z-G Hou, the Key Laboratory of Complex Systems and Intelligence Science, Inst. of Aut., The Chinese Ac. of Sc., Beijing).

Habilitation

[44] Bukovsky, I.: New Trends for Adaptive Systems and Evaluation of Complicated Dynamical Systems, Teze habilitační přednášky, Česká technika - nakladatelství ČVUT, October 2012.

[45] Bukovsky, I.: New Trends for Adaptive Systems and Evaluation of Complicated Dynamical Systems, Habilitation Thesis, Faculty of Mechanical Engineering, Czech Technical University in Prague (defended October 4, 2012).

Ph.D. Thesis (Werner von Siemens Excellence Award 2007)

[46] Bukovsky, I.: Modeling of Complex Dynamic Systems by Nonconventional Artificial Neural Architectures and Adaptive Approach to Evaluation of Chaotic Time Series, Ph.D. THESIS, Faculty of Mechanical Engineering, Czech Technical University in Prague (defended September 7, 2007).

Master Thesis

[47] Bukovsky, I.: Analysis of Cardiovascular System Model and the Interpretation of Chaotic phenomena in Signals ECG and HRV. Diploma Thesis, Faculty of Mechanical Engineering, CTU in Prague, 2002.

Memberships

- IEEE CIS Neural Networks Technical Committee (2007, 08, 09, 10, 11,12)

- IEEE CIS NNTC Task Force on Education (chair 2009, 2010, 2011,12)

- IEEE CIS Student Activity Subcommittee (Vice Chair 2010, 11, 12)

- Graduate Student Research Grants (2011,13)

Workshop Organization

- CompSens 2011, IEEE Workshop on Merging Fields of Computational Intelligence and Sensor Technology, within the IEEE Symposium Series on Computational Intelligence 2011, Paris, 2011.

Special Session Organization

- I. Bukovsky, T. Wagner, J. Pitel,: IEEE CompSens 2013, session on Merging Fields of Computational Intelligence and Sensor Technology, within the IEEE Symposium Series on Computational Intelligence 2013, Singapore, 2013.

- S.Y. Fu, N. Homma, I. Bukovsky, A.M.G. Solo, and M.M. Gupta: Biologically Inspired Sensing, Computing and Control Session, within the The seventh International Conference on Intelligent Systems and Knowledge Engineering (ISKE2012), Beijing, China, 2012.

Editorial

- Cognitive and Neural Aspects in Robotics 2012, annual issue of Journal of Robotics, Hindawi Publishing Corporation

- Cognitive and Neural Aspects in Robotics 2011, annual issue of Journal of Robotics, Hindawi Publishing Corporation.

- A/E IEEE Transactions on Neural Networks, 2011.

- Cognitive and Neural Aspects in Robotics with Applications 2010, special issue on Journal of Robotics, Hindawi Publishing Corporation.

Conference Activities

- Program Committee of IEEE International Joint Conference on Neural Networks, USA, 2013.

- Program Committee of 12th IEEE International Conference on Cognitive Informatics & Cognitive Computing ICCI*CC, USA, 2013.

- Program Committee of 5^th International Conference on Neural Computation Theory and Applications (NCTA 2013), part of International Joint Conference on Computational Intelligence IJCCI, Portugal 2013.

- Program Committee of 14th EANN Conference, Engineering Applications of Neural Networks, Greece, 2013.

- Program Committee of The 25th International Conference on Software Engineering and Knowledge Engineering SEKE 2013 Boston, USA, 2013.

- Program Committee of 11^th IEEE International Conference on Cognitive Informatics & Cognitive Computing ICCI*CC Japan, 2012.

- Program Committee of 4th International Conference on Neural Computation Theory and Applications (NCTA 2012), Spain, 2012.

- Program Committee of 9th International Symposium on Neural Networks (ISNN 2012), China, 2012.

- Program Committee of IEEE 13th Engineering Applications of Neural Networks Conference (EANN 2012), London, UK, 2012.

- Program Committee of 9th International Symposium on Neural Networks (ISNN 2012), China, 2012.

- Program Committee of IEEE 13th Engineering Applications of Neural Networks Conference (EANN 2012), London, UK, 2012.

- Program Committee of IEEE 2011 International Joint Conference on Neural Networks USA, 2011.

- Program Committee of ICCI 2011,10th IEEE International Conference on Cognitive Informatics , Canada, 2011.

- Program Committee of 12th Engineering Applications of Neural Networks Conference (EANN), Greece, 2011

- Program Committee of CICA 2011 IEEE Symposium on Computational Intelligence in Control and Automation, Paris, 2011.

- Program Committee of ICNC 2011, International Conference on Natural Computation, China, 2011

- Technical Program Committee of IEEE IJCNN + chairing sections IA-1, SC, Spain, 2010

- Program Committee of ICANN 10 International Conference on Artificial Neural Networks, Greece, 2010.

- Program Committee of ICNC 2010, International Conference on Neural Computation, Spain, 2010.

- Program Committee of ICCI 2010, 9th IEEE International Conference on Cognitive Informatics , China, 2010.

- Program Committee of ICNC 2010, International Conference on Natural Computation, China, 2010.

- Program Committee of ICCI 2009, 8th IEEE International Conference on Cognitive Informatics , Hong Kong, 2009.

- Program Committee of ICANN 09 International Conference on Artificial Neural Networks, Cyprus, 2009.

- Program Committee of ICNC 2009, International Conference on Neural Computation, Portugal, 2009.

- Program Committee of ICNC 2009, International Conference on Natural Computation, China, 2009.

- Program Committee of CICA 2009, IEEE Symposium on Computational Intelligence in Control and Automation, Nashville, USA, 2009.

- Reviewer for the 17th International Conference on Nuclear Engineering (ICONE), ASME, 2009 (7x)

- Chairing 2 sections (MA-6, MP-2) at 2008 IEEE International Conference on Automation and Logistics, Qingdao, China, 2008.

- Panel discussion board member at ICCI 2008,  The 7th IEEE International Conference on Cognitive Informatics, California , USA, 2008.

- Program Committee of IJCNN 2008, the 2008 IEEE World Congress on Computational Intelligence (WCCI 2008), Hong Kong, June 1-6, 2008

- Technical Committee of FUZZ-IEEE 2008, WCCI 2008 Hong Kong, June 1-6, 2008

- Reviewer for the 16th International Conference on Nuclear Engineering (ICONE), ASME, 2008 (2x)

- Program Committee of 2007 ISNN International Symposium on Neural Networks, Nanjing, China, June 3-7, 2007

- Co-chairing the section “Automation, Intelligence and Robotics” during the 7th International FLINS Conference on Applied Artificial Intelligence, Genova, Italy, August 29-31, 2006

Journals Reviews

- IEEE Transactions on Neural Networks, 2010,11
- Nuclear Engineering and Design, 2009
- Soft Computing, 2009

- IEEE Transactions on Systems, Man, and Cybernetics--Part B: Cybernetics, 2007, 2008

- The International Journal of Cognitive Informatics and Natural Intelligence (IJCiNi), 2008, 2010(10x)

- IEEE Transactions on Control Systems Technology, 2007, 2009

- IEEE Computational Intelligence Magazine, 2006, 2008

- Automatizace, Czech Republic, 2006

Book chapter reviews

- Advances in Cognitive Informatics, LNAI, 2009 (1x) 
- Artificial Higher Order Neural Networks for Computer Science and Engineering: Trends for Emerging Applications, 2009 (1x)