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Relevant bibliographies by topics / Method of identification systems

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Academic literature on the topic 'Method of identification systems'

Author: Grafiati

Published: 28 May 2022

Last updated: 30 July 2025

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Journal articles on the topic "Method of identification systems"

1

LYSENKO, S., V. OMELIANENKO, and R. SHCHUKA. "METHOD FOR THE SPYWARE IDENTIFICATION IN THE COMPUTER SYSTEMS." Herald of Khmelnytskyi National University. Technical sciences 285, no. 3 (2020): 43–49. https://doi.org/10.31891/2307-5732-2020-285-3-7.

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The paper presents a method of identification of spyware identification software in computer systems, which allows detection of all types, and differs from the known ones, which provides the principle of proactivity and is based on mechanisms of machine learning. For the proposed method of identifying spyware, it uses an analysis of the behaviour of the software on computer systems. The method is also based on a downstream analysis of the involvement of machine learning apparatus, in particular reinforcement learning, which operates with concepts of stability values for the malware detection.

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Volkova, Natalya P., and Viktor N. Krylov. "HYBRID TEXTURE IDENTIFICATION METHOD." Herald of Advanced Information Technology 4, no. 2 (2021): 123–34. http://dx.doi.org/10.15276/hait.02.2021.2.

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The importance of the modeling mode in systems of computer visual pattern recognition is shown. The purpose of the mode is to determine the types of textures that are present on the images processed in intelligent diagnostic systems. Images processed in technical diagnostic systems contain texture regions, which can be represented by different types of textures - spectral, statistical and spectral-statistical. Texture identification methods, such as, statistical, spectral, expert, multifractal, which are used to identify and analyze texture images, have been analyzed. To determine texture regi

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Gorobets, Alexander. "STRUCTURAL IDENTIFICATION METHOD OF SIMULTANEOUS EQUATIONS SYSTEMS." IFAC Proceedings Volumes 35, no. 1 (2002): 191–94. http://dx.doi.org/10.3182/20020721-6-es-1901.01422.

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Galetta, Clement, Jean-Marc Roussel, and Jean-Marc Faure. "A relative identification method for reactive systems." IFAC-PapersOnLine 51, no. 7 (2018): 152–59. http://dx.doi.org/10.1016/j.ifacol.2018.06.294.

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Lyashevskiy, Sergey, Larry A. Abel, Sergey Lyashevskiy, and Larry A. Abel. "Nonlinear Systems Identification using the Lyapunov Method." IFAC Proceedings Volumes 27, no. 8 (1994): 271–76. http://dx.doi.org/10.1016/s1474-6670(17)47727-5.

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Niven, Robert, Ali Mohammad-Djafari, Laurent Cordier, Markus Abel, and Markus Quade. "Bayesian Identification of Dynamical Systems." Proceedings 33, no. 1 (2020): 33. http://dx.doi.org/10.3390/proceedings2019033033.

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Many inference problems relate to a dynamical system, as represented by dx/dt = f (x), where x ∈ ℝn is the state vector and f is the (in general nonlinear) system function or model. Since the time of Newton, researchers have pondered the problem of system identification: how should the user accurately and efficiently identify the model f – including its functional family or parameter values – from discrete time-series data? For linear models, many methods are available including linear regression, the Kalman filter and autoregressive moving averages. For nonlinear models, an assortment of mach

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Zhou, Hao, Wen Zuo, Yaojun Qiao, et al. "Ultrasonic phase extraction method for co-cable identification in coherent optical transmission systems." Chinese Optics Letters 22, no. 10 (2024): 100601. http://dx.doi.org/10.3788/col202422.100601.

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Sawaragi, Hiroshi, Jingwu Yao, and Sueo Sugimoto. "Identification of Multivariable State Feedback Systems Using the Indirect Identification method." Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications 1998 (May 5, 1998): 99–104. http://dx.doi.org/10.5687/sss.1998.99.

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Zuev, Alexander, Alexey Zhirabok, Vladimir Filaretov, and Alexander Protsenko. "Method of faults identification in non-stationary systems." Robotics and Technical Cybernetics 10, no. 1 (2022): 55–63. http://dx.doi.org/10.31776/rtcj.10106.

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The article presents a new method for faults identification in mechatronic systems, described by non-stationary nonlinear differential equations, in the presence of perturbations. Observers working in a sliding mode are used to solve the problem. The proposed approach is based on the idea of constructing a reduced (with lower dimension) model of the original system with selective sensitivity to faults and disturbances. The main purpose of introducing such a model is the ability to take into account the nonstationarity of the system. The stated theory is illustrated by a practical example. Key

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Janot, A. "Using the SDP identification method for electromechanical systems." IFAC-PapersOnLine 54, no. 7 (2021): 809–14. http://dx.doi.org/10.1016/j.ifacol.2021.08.461.

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Dissertations / Theses on the topic "Method of identification systems"

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Mao, Ke Zhi. "Nonlinear systems identification using the Narmax method." Thesis, University of Sheffield, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.310424.

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Fung, Jimmy Jr. "Parameter Identification of Nonlinear Systems Using Perturbation Methods and Higher-Order Statistics." Thesis, Virginia Tech, 1998. http://hdl.handle.net/10919/36921.

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A parametric identification procedure is proposed that combines the method of multiple scales and higher-order statistics to efficiently and accurately model nonlinear systems. A theoretical background for the method of multiple scales and higher-order statistics is given. Validation of the procedure is performed through applying it to numerical simulations of two nonlinear systems. The results show how the procedure can successfully characterize the system damping and nonlinearities and determine the corresponding parameters. The procedure is then applied to experimental measur

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Johnson, Amos Y. Jr. "A method for human identification using static, activity-specific parameters." Diss., Georgia Institute of Technology, 2002. http://hdl.handle.net/1853/15793.

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LISITANO, DOMENICO. "Spatial damping identification and control of mechanical systems." Doctoral thesis, Politecnico di Torino, 2019. http://hdl.handle.net/11583/2734827.

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Ullah, Naseem. "Disease modules identification in heterogenous diseases with WGCNA method." Thesis, Högskolan i Skövde, Institutionen för biovetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-16692.

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The widely collected and analyzed genetic data help in understanding the underlying mechanisms of heterogeneous diseases. Cellular components interact in a network fashion where genes are nodes and edges are the interactions. The failure in individual genes lead to dys-regulation of sub-groups of genes which causes a disease phenotype, and this dys-functional region is called a disease module. Disease module identification in complex diseases such as asthma and cancer is a huge challenge. Despite the development of numerous sophisticated methods there is a still no gold standard. In this study

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Tayamon, Soma. "Nonlinear System Identification and Control Applied to Selective Catalytic Reduction Systems." Doctoral thesis, Uppsala universitet, Avdelningen för systemteknik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-229148.

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The stringent regulations of emission levels from heavy duty vehicles create a demand for new methods for reducing harmful emissions from diesel engines. This thesis deals with the modelling of the nitrogen oxide (NOx) emissions from heavy duty vehicles using a selective catalyst as an aftertreatment system, utilising ammonia (NH3) for its reduction. The process of the selective catalytic reduction (SCR) is nonlinear, since the result of the chemical reactions involved depends on the load operating point and the temperature. The purpose of this thesis is to investigate different methods for no

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Larsson, Per. "Linear parameter varying model and identification method for Li-ion batteries in electric vehicles." Thesis, Uppsala universitet, Avdelningen för systemteknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-444687.

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The market for electric vehicles (EV) is growing rapidly. The rise of EVs is most prominent for passenger vehicles, but trucks and busses are also quickly becoming electrified. Scania aims to be the leader of this transition. A central part of the EV is the Lithium-ion battery. In order to use the battery in the most efficient manner a Battery Management System (BMS) is needed. A key part of the BMS is a model that describes the battery as a system where the input is the current and the output is the terminal voltage. The dynamics of the battery is affected by external factors, called scheduli

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Zhou, Ning. "Subspace methods of system identification applied to power systems." Laramie, Wyo. : University of Wyoming, 2005. http://proquest.umi.com/pqdweb?did=1095432761&sid=1&Fmt=2&clientId=18949&RQT=309&VName=PQD.

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McNabb, Patrick James. "Statistical method for identification of sources of electromechanical oscillations in power systems." Thesis, University of Edinburgh, 2011. http://hdl.handle.net/1842/9500.

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The use of real-time continuous dynamics monitoring often indicates dynamic behaviour that was not anticipated by model-based studies. In such cases it can be difficult to locate the sources of problems using conventional tools. This thesis details the possibility of diagnosing the causes of problems related to oscillatory stability using measurement-based data such as active power and mode decay time constant, derived from system models. The aim of this work was to identify dynamics problems independently of an analytical dynamic model, which should prove useful in diagnosing and correcting d

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Lei, Jun. "Static structural system identification using observability method." Doctoral thesis, Universitat Politècnica de Catalunya, 2018. http://hdl.handle.net/10803/650829.

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During the construction and operation stages of structures, various factors lead to irreversible degradation that could affect the normal use and the public safety of these structures. In recent years, it has been common to carry out condition assessment of structures using Structural System Identification (SSI) methods. SSI is the application of parameter estimation in structural system. One key issue in SSI is to guarantee the observability of the parameters to be estimated. This was already addressed by the SSI by Observability Method (OM) using static tests. However, a systematic analysi

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Books on the topic "Method of identification systems"

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Uciński, Dariusz. Optimal measurement methods for distributed parameter system identification. CRC Press, 2005.

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Deman, Tang, and Langley Research Center, eds. System identification and POD method applied to unsteady aerodynamics. National Aeronautics and Space Administration, Langley Research Center, 2001.

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Ossinger, Mary C. A method to identify, inventory, and map wetlands using aerial photography and geographic information systems. Washington State Dept. of Transportation, 1991.

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Sira-Ramírez, Hebertt, Carlos García-Rodríguez, John Cortés-Romero, and Alberto Luviano-Juárez. Algebraic Identification and Estimation Methods in Feedback Control Systems. John Wiley & Sons, Ltd, 2014. http://dx.doi.org/10.1002/9781118730591.

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Derbel, Nabil, and Quanmin Zhu, eds. Modeling, Identification and Control Methods in Renewable Energy Systems. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-1945-7.

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United States. National Aeronautics and Space Administration., ed. System identification of damped truss-like space structures. National Aeronautics and Space Administration, 1995.

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Tammi, Kari. Active control of radial rotor vibrations: Identification, feedback, feedforward, and repetitive control methods. VTT Technical Research Centre of Finland, 2007.

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Center, Langley Research, ed. Shape identification technique for a two-dimensional elliptic system by boundary integral equation method. National Aeronautics and Space Administration, Langley Research Center, 1989.

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B, Marks Virginia, Keckler Claude R, and Langley Research Center, eds. NASA Workshop on Distributed Parameter Modeling and Control of Flexible Aerospace Systems: Proceedings of a workshop sponsored by tne National Aeronautics and Space Administration, Washington, D.C. and held in Williamsburg, Virginia, June 8-10, 1992. National Aeronautics and Space Administration, Langley Research Center, 1994.

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NASA Workshop on Distributed Parameter Modeling and Control of Flexible Aerospace Systems (1992 Williamsburg, Va.). NASA Workshop on Distributed Parameter Modeling and Control of Flexible Aerospace Systems: Proceedings of a workshop sponsored by the National Aeronautics and Space Administration, Washington, D.C. and held in Williamsburg, Virginia, June 8-10, 1992. National Aeronautics and Space Administration, Langley Research Center, 1994.

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Book chapters on the topic "Method of identification systems"

1

Jiang, Z. H., and W. Schaufelberger. "Recursive block pulse function method." In Identification of Continuous-Time Systems. Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-011-3558-0_7.

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Marchenko, Oleksandr, Anatoly Anisimov, Andrii Nykonenko, Tetiana Rossada, and Egor Melnikov. "Machine Learning Method for Paraphrase Identification." In Flexible Query Answering Systems. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-59692-1_14.

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Feng, Jun-Kang. "A Method for Entity Identification." In Critical Issues in Systems Theory and Practice. Springer US, 1995. http://dx.doi.org/10.1007/978-1-4757-9883-8_44.

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Kuchkarova, Dilarom F., and Dilnoza A. Achilova. "Identification Method of Topographic Surfaces Models." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-95588-9_71.

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Mahmoud, Magdi S., and Yuanqing Xia. "System Identification Methods." In Applied Control Systems Design. Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-2879-3_3.

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Isermann, Rolf, and Marco Münchhof. "Subspace Methods." In Identification of Dynamic Systems. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-540-78879-9_16.

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Ammar, G., D. Cheng, W. Dayawansa, and C. Martin. "Identification of Linear Systems by Prony’s Method." In Robust Control of Linear Systems and Nonlinear Control. Birkhäuser Boston, 1990. http://dx.doi.org/10.1007/978-1-4612-4484-4_47.

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Padmavathi, S., C. Rajalaxmi, and K. P. Soman. "Texel Identification Using K-Means Clustering Method." In Advances in Intelligent Systems and Computing. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30111-7_27.

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Takcı, Hidayet, and İbrahim Soğukpınar. "Letter Based Text Scoring Method for Language Identification." In Advances in Information Systems. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30198-1_29.

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Aoshima, N. "Microprocessor-Based System Identification by Signal Compression Method." In Microprocessor-Based Control Systems. Springer Netherlands, 1986. http://dx.doi.org/10.1007/978-94-009-4708-5_5.

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Conference papers on the topic "Method of identification systems"

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Dai, Zhengchen, Jinxia Liu, Zhiwen Cui, and Tribikram Kundu. "A damage identification method using multimodal Lamb waves." In Health Monitoring of Structural and Biological Systems XIX, edited by Piervincenzo Rizzo, Zhongqing Su, Fabrizio Ricci, and Kara J. Peters. SPIE, 2025. https://doi.org/10.1117/12.3049475.

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Wang, Luyao, Libin Chen, Zhiwei Yang, Kewei Yang, and Qingqing Yang. "DRLKHN: A Self-Learning Heterogeneous Network Key Nodes Identification Method." In 2024 World Conference on Complex Systems (WCCS). IEEE, 2024. https://doi.org/10.1109/wccs62745.2024.10765526.

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Asafusa, Yohei, and Takashi Yoshimi. "A Study of Dialect Identification Method Using Phoneme Texts." In 2024 24th International Conference on Control, Automation and Systems (ICCAS). IEEE, 2024. https://doi.org/10.23919/iccas63016.2024.10773287.

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Liu, Xiao, Sudan Han, and Jinlin Peng. "Complex Electromagnetic Space Combat System-of-systems Modeling and Key Node Identification Method." In 2024 International Annual Conference on Complex Systems and Intelligent Science (CSIS-IAC). IEEE, 2024. https://doi.org/10.1109/csis-iac63491.2024.10919398.

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Muranov, A. N., A. P. Titova, and M. H. Nogmov. "Stopping Method for Iterative Scene Identification in an Image Stream." In 2024 Dynamics of Systems, Mechanisms and Machines (Dynamics). IEEE, 2024. https://doi.org/10.1109/dynamics64718.2024.10838681.

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Wang, Yueyang, and Bahram Shafai. "A Subspace System Identification Method for Positive Systems." In 2023 9th International Conference on Control, Decision and Information Technologies (CoDIT). IEEE, 2023. http://dx.doi.org/10.1109/codit58514.2023.10284341.

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Liu, Chang, Ming Yu, and Yu Zhang. "A Nonparametric Multivariate Method for Performance Analysis of Virtual Machines in Cloud Computing Systems." In Modelling, Identification and Control. ACTAPRESS, 2014. http://dx.doi.org/10.2316/p.2014.809-048.

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Alayyan, F. O., Yee Hong Leung, and A. M. Zoubir. "A Fast Blind Channel Estimation Method For ZP-OFDM Systems." In 2005 Microwave Electronics: Measurements, Identification, Applications. IEEE, 2005. http://dx.doi.org/10.1109/ssp.2005.1628676.

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Asgari, Mohammad H., B. Khaki, A. Mozdawar, and R. Riahi. "A new method for evaluation Market Power and identification of dominant suppliers in reactive power markets." In 2009 3rd Annual IEEE Systems Conference. IEEE, 2009. http://dx.doi.org/10.1109/systems.2009.4815834.

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Byrski, Witold, and Jędrzej Byrski. "The Improvement of Modulating Function Method for Fast Identification of Parameter Faults in Linear Continuous Systems." In Modelling, Identification and Control. ACTAPRESS, 2012. http://dx.doi.org/10.2316/p.2012.769-015.

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Reports on the topic "Method of identification systems"

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Jung, Kiwook, Katherine Morris, Kevin W. Lyons, Swee Leong, and Hyunbo Cho. Performance Challenges Identification Method for Smart Manufacturing Systems. National Institute of Standards and Technology, 2016. http://dx.doi.org/10.6028/nist.ir.8108.

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Burns, John A., Eugene M. Cliff, and Lizette Zietsman. Computational Methods for Identification, Optimization and Control of PDE Systems. Defense Technical Information Center, 2010. http://dx.doi.org/10.21236/ada523367.

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Nandanoori, Sai Pushpak, Kristine Arthur-Durett, Alejandro Heredia-Langner, and Thomas Edgar. A Data-driven approach to Determining the Fidelity in the Hardware-in-the-loop Systems using Subspace Identification Method. Office of Scientific and Technical Information (OSTI), 2024. http://dx.doi.org/10.2172/2325016.

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Rosen, I. G. Approximation Theory and Computational Methods for the Identification and Control of Distributed Parameter Systems. Defense Technical Information Center, 1993. http://dx.doi.org/10.21236/ada277335.

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Burks, Thomas F., Victor Alchanatis, and Warren Dixon. Enhancement of Sensing Technologies for Selective Tree Fruit Identification and Targeting in Robotic Harvesting Systems. United States Department of Agriculture, 2009. http://dx.doi.org/10.32747/2009.7591739.bard.

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The proposed project aims to enhance tree fruit identification and targeting for robotic harvesting through the selection of appropriate sensor technology, sensor fusion, and visual servo-control approaches. These technologies will be applicable for apple, orange and grapefruit harvest, although specific sensor wavelengths may vary. The primary challenges are fruit occlusion, light variability, peel color variation with maturity, range to target, and computational requirements of image processing algorithms. There are four major development tasks in original three-year proposed study. First, s

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Levisohn, Sharon, Maricarmen Garcia, David Yogev, and Stanley Kleven. Targeted Molecular Typing of Pathogenic Avian Mycoplasmas. United States Department of Agriculture, 2006. http://dx.doi.org/10.32747/2006.7695853.bard.

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Intraspecies identification (DNA "fingerprinting") of pathogenic avian mycoplasmas is a powerful tool for epidemiological studies and monitoring strain identity. However the only widely method available for Mycoplasma gallisepticum (MG) and M. synoviae (MS)wasrandom amplified polymorphic DNA (RAPD). This project aimed to develop alternative and supplementary typing methods that will overcome the major constraints of RAPD, such as the need for isolation of the organism in pure culture and the lack of reproducibility intrinsic in the method. Our strategy focussed on recognition of molecular mark

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WANG, MIN, Sheng Chen, Changqing Zhong, et al. Diagnosis using artificial intelligence based on the endocytoscopic observation of the gastrointestinal tumours: a systematic review and meta-analysis. InPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2023. http://dx.doi.org/10.37766/inplasy2023.2.0096.

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Review question / Objective: With the development of endoscopic techniques, several diagnostic endoscopy methods are available for the diagnosis of malignant lesions, including magnified pigmented endoscopy and narrow band imaging (NBI).The main goal of endoscopy is to achieve the real-time diagnostic evaluation of the tissue, allowing an accurate assessment comparable to histopathological diagnosis based on structural and cellular heterogeneity to significantly improve the diagnostic rate for cancerous tissues. Endocytoscopy (ECS) is based on ultrahigh magnification endoscopy and has been app

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Kress, Marin, Patricia DiJoseph, Morgan Johnston, et al. A method for evaluating Automatic Identification System (AIS) coverage on select inland waterways in 2020 and 2021 : Upper Mississippi River, Illinois River, and Ohio River. Engineer Research and Development Center (U.S.), 2023. http://dx.doi.org/10.21079/11681/47839.

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The Automatic Identification System (AIS) shares vessel position information for navigational safety purposes. AIS broadcasts are received by other ships and terrestrial stations; however, in some areas there is no, or low, terrestrial station coverage to receive broadcasts. The US Army Corps of Engineers (USACE) developed an Online Travel Time Atlas (OTTA) to process AIS data and derive a transit count. This study examined OTTA output from 2020 and 2021 to identify areas of high or low AIS coverage along the Upper Mississippi, Illinois, and Ohio Rivers. Segments with a yearly average of two o

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Grumet, Rebecca, and Benjamin Raccah. Identification of Potyviral Domains Controlling Systemic Infection, Host Range and Aphid Transmission. United States Department of Agriculture, 2000. http://dx.doi.org/10.32747/2000.7695842.bard.

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Potyviruses form one of the largest and most economically important groups of plant viruses. Individual potyviruses and their isolates vary in symptom expression, host range, and ability to overcome host resistance genes. Understanding factors influencing these biological characteristics is of agricultural importance for epidemiology and deployment of resistance strategies. Cucurbit crops are subject to severe losses by several potyviruses including the highly aggressive and variable zucchini yellow mosaic virus (ZYMV). In this project we sought to investigate protein domains in ZYMV that infl

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González, Javier, Dante Castillo-Canales, Monserrat Creamer, and Magali Ramos Jarrin. Misalignments and Incoherencies within Ecuador's Education System: How Well Are Key Actors and Public Efforts Aligned towards Better Learning Outcomes? Research on Improving Systems of Education (RISE), 2023. http://dx.doi.org/10.35489/bsg-rise-wp_2023/137.

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This study aims to identify the main critical misalignments and inconsistencies nested in the Ecuadorian education system, which inhibit and limit its capacity to transform efforts, resources, and reforms into better learning outcomes for all students. To do so, it uses an innovative methodology developed by the RISE (Research on Improving Systems of Education) programme based on a 'Systems Thinking' perspective. This approach allows the analysis of key actors, their incentives, and interactions, to assess the overall alignment of the system and the existence of barriers that might prevent the

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