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Статті в журналах з теми "System identification- Geophysical signals"
Lubis, Muhammad Zainuddin, Kasih Anggraini, Husnul Kausarian, and Sri Pujiyati. "Review: Marine Seismic And Side-Scan Sonar Investigations For Seabed Identification With Sonar System." Journal of Geoscience, Engineering, Environment, and Technology 2, no. 2 (June 1, 2017): 166. http://dx.doi.org/10.24273/jgeet.2017.2.2.253.
Повний текст джерелаAbramovych, А. О. "IMPROVING THE EDDY CURRENT IDENTIFIER OF METALS BASED ON THE CORRELATION APPROACH." Radio Electronics, Computer Science, Control, no. 4 (December 3, 2022): 7. http://dx.doi.org/10.15588/1607-3274-2022-4-1.
Повний текст джерелаAbazarsa, Fariba, Fariborz Nateghi, S. Farid Ghahari, and Ertugrul Taciroglu. "Blind Modal Identification of Non-Classically Damped Systems from Free or Ambient Vibration Records." Earthquake Spectra 29, no. 4 (November 2013): 1137–57. http://dx.doi.org/10.1193/031712eqs093m.
Повний текст джерелаBodin, Jacques, Gilles Porel, Benoît Nauleau, and Denis Paquet. "Delineation of discrete conduit networks in karst aquifers via combined analysis of tracer tests and geophysical data." Hydrology and Earth System Sciences 26, no. 6 (April 1, 2022): 1713–26. http://dx.doi.org/10.5194/hess-26-1713-2022.
Повний текст джерелаAkhi, A. V. "Akhi A.V. Efficiency of Identification of Complex Noise-Like Signal Classes by Dolphins (<i>Tursiops truncatus</i>) under Simultaneous Presentation Spatial Uncertainty." Fundamental and Applied Hydrophysics 16, no. 1 (April 23, 2023): 90–97. http://dx.doi.org/10.59887/fpg/vxe3-6531-nkup.
Повний текст джерелаKOH, C. G., and M. J. PERRY. "STRUCTURAL DAMAGE QUANTIFICATION BY SYSTEM IDENTIFICATION." Journal of Earthquake and Tsunami 01, no. 03 (September 2007): 211–31. http://dx.doi.org/10.1142/s1793431107000134.
Повний текст джерелаZamora Santacruz, Mario Fernando, Mario RUIZ, and Jose OSORNO. "The Exploration of Hydrocarbons and Mining & Energy Resources Using Non-Seismic Methods - Nuclear Magnetic Resonance Technology." Technium: Romanian Journal of Applied Sciences and Technology 2, no. 7 (December 22, 2020): 372–89. http://dx.doi.org/10.47577/technium.v2i7.2258.
Повний текст джерелаMunoz-Martin, Joan Francesc, Raul Onrubia, Daniel Pascual, Hyuk Park, Adriano Camps, Christoph Rüdiger, Jeffrey Walker, and Alessandra Monerris. "Untangling the Incoherent and Coherent Scattering Components in GNSS-R and Novel Applications." Remote Sensing 12, no. 7 (April 9, 2020): 1208. http://dx.doi.org/10.3390/rs12071208.
Повний текст джерелаKaczmarek, Adrian, and Bernard Kontny. "Identification of the Noise Model in the Time Series of GNSS Stations Coordinates Using Wavelet Analysis." Remote Sensing 10, no. 10 (October 10, 2018): 1611. http://dx.doi.org/10.3390/rs10101611.
Повний текст джерелаSteinitz, G., P. Kotlarsky, and O. Piatibratova. "Indications for influence of artificial (man-made) activity on radon signals, in simulation experiments." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 472, no. 2195 (November 2016): 20160311. http://dx.doi.org/10.1098/rspa.2016.0311.
Повний текст джерелаДисертації з теми "System identification- Geophysical signals"
AlHilal, M. H. "System identification using pseudorandom signals." Thesis, Swansea University, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.635747.
Повний текст джерелаSolomou, Michael. "System identification in the presence of nonlinear distortions using multisine signals." Thesis, University of South Wales, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.289160.
Повний текст джерелаDeng, Qingwei 1968. "Identification of dendritic targeting signals of voltage-gated potassium channel 3." Thesis, McGill University, 2004. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=82219.
Повний текст джерелаPIOLDI, Fabio. "Time and Frequency Domain output-only system identification from earthquake-induced structural response signals." Doctoral thesis, Università degli studi di Bergamo, 2017. http://hdl.handle.net/10446/77137.
Повний текст джерелаSpeckhahn, Marcus M. "Identification of acoustically active Arctic pressure ridges through the use of RADARSAT Geophysical Processor System (RGPS) sea ice products." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1998. http://handle.dtic.mil/100.2/ADA351618.
Повний текст джерела"June 1998." Thesis advisor(s): Robert H. Bourke, James H. Wilson. Includes bibliographical references (p. 301-304). Also available online.
Tuffner, Francis K. "Computationally efficient weighted updating of statistical parameter estimates for time varying signals with application to power system identification." Laramie, Wyo. : University of Wyoming, 2008. http://proquest.umi.com/pqdweb?did=1674094221&sid=4&Fmt=2&clientId=18949&RQT=309&VName=PQD.
Повний текст джерелаKuramoto, André Seichi Ribeiro. "Projeto de sinais de excitação para identificação multivariável de plantas industriais." Universidade de São Paulo, 2012. http://www.teses.usp.br/teses/disponiveis/3/3139/tde-07112016-144658/.
Повний текст джерелаIn this work methods for generating sets of excitation signals for system identification are discussed and evaluated. This study is focused on applications in the process industries, particularly in oil refining. The operational constraints of the oil refining industry are becoming increasingly severe due to increased energy demand, quality of products, oil price variations,market competition and other economic, environmental and energy efficiency factors. In this scenario the use of model predictive control techniques is increasing, thus the demand for plant identification as well. The particular characteristics of the processing plants impose restrictions to the project and application of excitation signals. Various methods for generating signals accessible in the literature and three new others proposed in this work are compared with reference to these restrictions. One of the main constraints for applying excitation signals for identification is relative to the period available for excitation of the plant. Thus, for the proper use of this time interval, it is necessary to ensure the success of an experiment prior to its implementation. In the literature there are several performance measurements for evaluation of sets of excitation signals prior to the experiment. This work proposes two new measures to complement the evaluation. The effectiveness of the generating methods and performance measurements for excitation signals is evaluated by simulation of multivariable identification of two typical oil refining plants. The conclusions of this work briefly present these evaluations, as well as some suggestions of future work for the continuity of the current research.
LIMA, Rafael Bezerra Correia. "Metodologia para identificação de sistemas em espaço de estados por meio de excitações pulsadas." Universidade Federal de Campina Grande, 2016. http://dspace.sti.ufcg.edu.br:8080/jspui/handle/riufcg/1287.
Повний текст джерелаMade available in DSpace on 2018-07-30T14:13:06Z (GMT). No. of bitstreams: 1 RAFAEL BEZERRA CORREIA LIMA - TESE PPGEE 2016..pdf: 2324960 bytes, checksum: db1b63193864e8e19bcba191952df2b9 (MD5) Previous issue date: 2016-09-20
Nesse trabalho são apresentadas contribuições na área de identificação de sistemas representados em espaço de estados. E proposta uma metodologia completa para estimação de modelos que representem as principais dinâmicas de processos industriais. O fluxo natural das procedimentos de identificação consiste da coleta experimental dos dados, seguido pela escolha dos modelos candidatos e da utilização de um critério de ajuste que selecione o melhor modelo possível. Nesse sentido é proposta uma metodologia para estimativa de modelos em espaço de estados, utilizando excitações pulsadas. A abordagem desenvolvida combina algoritmos precisos e eficientes com experimentos rápidos, adequados a ambientes industriais. O projeto das excitações é realizado em tempo real, por meio de informações coletadas em um curto experimento inicial, baseado em uma única oscilação de uma estrutura realimentada por um relê. Esse mecanismo possibilita uma estimativa preliminar do atraso e da constante de tempo dominante do sistema. O método de identificação proposto é baseado na teoria de realizações de Kalman. É apresentada uma reformulação do problema de realizações clássico, para comportar sinais de entrada pulsados. Essa abordagem se mostra computacionalmente eficiente, assim como apresenta resultados semelhantes aos métodos de benehmark. A técnica possibilita também a estimativa de atrasos de transporte e a inserção de conhecimentos prévios por meio de um problema de otimização com restrições via LMI Linear Matrix Incqualities. Em muitos casos, somente as características principais do sistema são relevantes em um projeto de sistema de controle. Portanto é proposta uma técnica para obtenção de modelos de primeira ordem com atraso, a partir da redução de modelos balanceados em espaço de estados. Por fim, todas as contribuições discutidas nesse trabalho de tese são validadas em uma série de plantas experimentais em escala de laboratório. Plantas essas, projetadas e construídas com o intuito de emular o cotidiano operacional de instalações industriais reais.
This work Íntroduces contributions related to thc field of systems identification of state space models. It is proposed a complete methodology for modei estimation that encompasses the main dynamics of industrial processes. The natural flxix of the identification procedures rests on the the empirical collection of data followed by the choice of candidate modela and posterior use ot an adjusting criteria that drafts the best model amoug the contenders. In this sense. a uew methodology is proposed for models estimation in state spaces using pulsed excitation signal. The developed approach combines accurate and efhcient algorithms with quick experíments whose are suitable for the industrial environment. The excitatiou design is performed in real time by means of information collected in a snort mitíai experíment based in an single oscillation of a relay feedback. This mechanism allows a preliminary estimation of both delay and time constant prevalent in the system. The identification method proposed is based on Kalmairs realization theory. The thesis íntroduces a reformulation of the classic realization problem so it can admit pulsed input signals. This approaíth show itself as computationally efficient as well as provides similar results eompared to those obtained when perfonning the benchmark methods. Moreover, the technic allows the transport delay estimation and insertion of prior knowledge by means of an optimization problem with restrictions via linear matrix inequalities restrictions. In many cases only the characteristics of the main system are relevant in control systems design. Therefore a technique for the attainment first order models with time delay based on balanced state space models reduction. Lastly ali the contributions provided aíong the thesis are discussed and validated in a series of pilot scale plants. designed and built to emulate the operational cycle in real industrial plants.
Kasaei, Shohreh. "Fingerprint analysis using wavelet transform with application to compression and feature extraction." Thesis, Queensland University of Technology, 1998. https://eprints.qut.edu.au/36053/7/36053_Digitised_Thesis.pdf.
Повний текст джерелаKarthikeyan, E. "Studies of system identification and denoising for geophysical signals." Thesis, 2018. http://eprint.iitd.ac.in:80//handle/2074/7928.
Повний текст джерелаКниги з теми "System identification- Geophysical signals"
Keith, Godfrey, ed. Perturbation signals for system identification. New York: Prentice Hall, 1993.
Знайти повний текст джерелаCoca, D. Smoothing chaotic signals for system identification: A multiresolution wavelet decomposition approach. Sheffield: University of Sheffield, Department of Automatic Control and Systems Engineering, 1995.
Знайти повний текст джерелаProgri, Ilir. Geolocation of RF signals: Principles and simulations. New York: Springer, 2011.
Знайти повний текст джерелаSpeckhahn, Marcus M. Identification of acoustically active Arctic pressure ridges through the use of RADARSAT Geophysical Processor System (RGPS) sea ice products. Monterey, Calif: Naval Postgraduate School, 1998.
Знайти повний текст джерелаOgunfunmi, Tokunbo. Adaptive Nonlinear System Identification: The Volterra and Wiener Model Approaches (Signals and Communication Technology). Springer, 2007.
Знайти повний текст джерелаAdaptive Nonlinear System Identification: The Volterra and Wiener Model Approaches (Signals and Communication Technology). Springer, 2007.
Знайти повний текст джерелаProgri, Ilir. Geolocation of RF Signals: Principles and Simulations. Springer, 2011.
Знайти повний текст джерелаProgri, Ilir. Geolocation of RF Signals: Principles and Simulations. Springer, 2014.
Знайти повний текст джерелаProgri, Ilir. Geolocation of RF Signals: Principles and Simulations. Springer, 2011.
Знайти повний текст джерелаIdentification of Acoustically Active Arctic Pressure Ridges Through theUse of RADARSAT Geophysical Processor System (RGPS) Sea Ice Products. Storming Media, 1998.
Знайти повний текст джерелаЧастини книг з теми "System identification- Geophysical signals"
Haber, Robert, and László Keviczky. "Test Signals for Identification." In Nonlinear System Identification — Input-Output Modeling Approach, 119–98. Dordrecht: Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-011-4481-0_2.
Повний текст джерелаTan, Ai Hui, and Keith Richard Godfrey. "Design of Pseudorandom Signals for Linear System Identification." In Industrial Process Identification, 25–58. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-03661-4_2.
Повний текст джерелаTan, Ai Hui, and Keith Richard Godfrey. "Design of Computer-Optimised Signals for Linear System Identification." In Industrial Process Identification, 59–94. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-03661-4_3.
Повний текст джерелаLingener, A. "Determination of Frequency Responses by Means of Pseudorandom Signals." In Application of System Identification in Engineering, 483–97. Vienna: Springer Vienna, 1988. http://dx.doi.org/10.1007/978-3-7091-2628-8_13.
Повний текст джерелаPillonetto, Gianluigi, Tianshi Chen, Alessandro Chiuso, Giuseppe De Nicolao, and Lennart Ljung. "Classical System Identification." In Regularized System Identification, 17–31. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95860-2_2.
Повний текст джерелаDe Moor, Bart, Peter Van Overschee, and Wouter Favoreel. "Algorithms for Subspace State-Space System Identification: An Overview." In Applied and Computational Control, Signals, and Circuits, 247–311. Boston, MA: Birkhäuser Boston, 1999. http://dx.doi.org/10.1007/978-1-4612-0571-5_6.
Повний текст джерелаMarkovsky, Ivan, Anton Amann, and Sabine Van Huffel. "Application of Filtering Methods for Removal of Resuscitation Artifacts from Human ECG Signals." In System Identification, Environmental Modelling, and Control System Design, 273–91. London: Springer London, 2012. http://dx.doi.org/10.1007/978-0-85729-974-1_14.
Повний текст джерелаBo, L. I. U., Z. H. A. O. Jun, and Q. I. A. N. Jixin. "Design and Analysis of Test Signals for System Identification." In Computational Science – ICCS 2006, 593–600. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11758532_78.
Повний текст джерелаWestwick, David T., and Robert E. Kearney. "Identification of Multiple-Input Nonlinear Systems Using Non-White Test Signals." In Advanced Methods of Physiological System Modeling, 163–78. Boston, MA: Springer US, 1994. http://dx.doi.org/10.1007/978-1-4757-9024-5_8.
Повний текст джерелаFaghih, Rose T. "From Physiological Signals to Pulsatile Dynamics: A Sparse System Identification Approach." In Dynamic Neuroscience, 239–65. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-71976-4_10.
Повний текст джерелаТези доповідей конференцій з теми "System identification- Geophysical signals"
Palma, Gabriel, Ana Aquino, Patricia Monticelli, Luciano Verdade, Charles Markham, and Rafael Moral. "A machine vision system for avian song classification with CNN’s." In 24th Irish Machine Vision and Image Processing Conference. Irish Pattern Recognition and Classification Society, 2022. http://dx.doi.org/10.56541/mhzn4111.
Повний текст джерелаTristanov, Alexander, Olga Lukovenkova, Yuri Marapulets, and Alina Kim. "Improvement of methods for sparse model identification of pulsed geophysical signals." In 2019 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA). IEEE, 2019. http://dx.doi.org/10.23919/spa.2019.8936817.
Повний текст джерелаTsumura, K., and J. Maciejowski. "Optimal quantization of signals for system identification." In 2003 European Control Conference (ECC). IEEE, 2003. http://dx.doi.org/10.23919/ecc.2003.7085053.
Повний текст джерела"Identification of sediment-related disaster based on seismic and acoustic signals ("MM-Identification")." In Earth System Sciences (ESS). Vienna: Austrian Academy of Sciences Press, 2018. http://dx.doi.org/10.1553/ess-mmidentifications1.
Повний текст джерелаNaik, Manjish, and Douglas Cochran. "Nonlinear system identification using compressed sensing." In 2012 46th Asilomar Conference on Signals, Systems and Computers. IEEE, 2012. http://dx.doi.org/10.1109/acssc.2012.6489039.
Повний текст джерелаBhat, Harish S. "System Identification via the Adjoint Method." In 2021 55th Asilomar Conference on Signals, Systems, and Computers. IEEE, 2021. http://dx.doi.org/10.1109/ieeeconf53345.2021.9723391.
Повний текст джерелаMatta, Rafik, Johnny K. H. Lau, Foteini Agrafioti, and Dimitrios Hatzinakos. "Real-time continuous identification system using ECG signals." In 2011 24th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE). IEEE, 2011. http://dx.doi.org/10.1109/ccece.2011.6030676.
Повний текст джерелаBingham, Jeffrey T., and Marco P. Schoen. "Characterization of Myoelectric Signals Using System Identification Techniques." In ASME 2004 International Mechanical Engineering Congress and Exposition. ASMEDC, 2004. http://dx.doi.org/10.1115/imece2004-59904.
Повний текст джерелаPapi, F., D. Tarchi, M. Vespe, F. Oliveri, and G. Aulicino. "Radiolocation and tracking of automatic identification system signals." In 2014 IEEE Statistical Signal Processing Workshop (SSP). IEEE, 2014. http://dx.doi.org/10.1109/ssp.2014.6884686.
Повний текст джерелаMurphy, K. "System identification and modelling of a milk pasteurisation plant." In Irish Signals and Systems Conference 2004. IEE, 2004. http://dx.doi.org/10.1049/cp:20040592.
Повний текст джерелаЗвіти організацій з теми "System identification- Geophysical signals"
Corriveau, L., J. F. Montreuil, O. Blein, E. Potter, M. Ansari, J. Craven, R. Enkin, et al. Metasomatic iron and alkali calcic (MIAC) system frameworks: a TGI-6 task force to help de-risk exploration for IOCG, IOA and affiliated primary critical metal deposits. Natural Resources Canada/CMSS/Information Management, 2021. http://dx.doi.org/10.4095/329093.
Повний текст джерелаPhillips, Donald, and Yoram Kapulnik. Using Flavonoids to Control in vitro Development of Vesicular Arbuscular Mycorrhizal Fungi. United States Department of Agriculture, January 1995. http://dx.doi.org/10.32747/1995.7613012.bard.
Повний текст джерелаLers, Amnon, and Gan Susheng. Study of the regulatory mechanism involved in dark-induced Postharvest leaf senescence. United States Department of Agriculture, January 2009. http://dx.doi.org/10.32747/2009.7591734.bard.
Повний текст джерелаWagner, D. Ry, Eliezer Lifschitz, and Steve A. Kay. Molecular Genetic Analysis of Flowering in Arabidopsis and Tomato. United States Department of Agriculture, May 2002. http://dx.doi.org/10.32747/2002.7585198.bard.
Повний текст джерела