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Статті в журналах з теми "Supervision signal"
Li, Teng, Huan Chang, and Jun Wu. "Nonnegative Signal Decomposition with Supervision." Mathematical Problems in Engineering 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/620537.
Повний текст джерелаGao, Hongliang, Xiaoling Li, Chao Gao, and Jie Wu. "Neural Network Supervision Control Strategy for Inverted Pendulum Tracking Control." Discrete Dynamics in Nature and Society 2021 (March 23, 2021): 1–14. http://dx.doi.org/10.1155/2021/5536573.
Повний текст джерелаKim, Byung-Gyu, and Dong-San Jun. "Artificial Intelligence for Multimedia Signal Processing." Applied Sciences 12, no. 15 (July 22, 2022): 7358. http://dx.doi.org/10.3390/app12157358.
Повний текст джерелаWeispfenning, Thomas. "Model and Signal Based Supervision of Components of Cars." IFAC Proceedings Volumes 30, no. 8 (June 1997): 479–84. http://dx.doi.org/10.1016/s1474-6670(17)43867-5.
Повний текст джерелаTumanyan, Narek T. "Deep Learning Approaches for Voice Emotion Recognition Using Sentiment-Arousal Space." Mathematical Problems of Computer Science 56 (December 14, 2021): 35–47. http://dx.doi.org/10.51408/1963-0077.
Повний текст джерелаHan, Haopeng, Eva Oberacker, Andre Kuehne, Shuailin Wang, Thomas Wilhelm Eigentler, Eckhard Grass, and Thoralf Niendorf. "Multi-Channel RF Supervision Module for Thermal Magnetic Resonance Based Cancer Therapy." Cancers 13, no. 5 (February 28, 2021): 1001. http://dx.doi.org/10.3390/cancers13051001.
Повний текст джерелаPedrycz, Witold, and George Vukovich. "Fuzzy clustering with supervision." Pattern Recognition 37, no. 7 (July 2004): 1339–49. http://dx.doi.org/10.1016/j.patcog.2003.11.005.
Повний текст джерелаRasztovits-Wiech, M., K. Studer, and W. R. Leeb. "Bit error probability estimation algorithm for signal supervision in all-optical networks." Electronics Letters 35, no. 20 (1999): 1754. http://dx.doi.org/10.1049/el:19991176.
Повний текст джерелаMinarčík, Peter, Hynek Procházka, and Martin Gulan. "Advanced Supervision of Smart Buildings Using a Novel Open-Source Control Platform." Sensors 21, no. 1 (December 29, 2020): 160. http://dx.doi.org/10.3390/s21010160.
Повний текст джерелаWang, Tiantian, Junjie Liu, Chuan Wan, and Zhi Wang. "Remote supervision strategy based on in-use vehicle OBD data flow." E3S Web of Conferences 268 (2021): 01007. http://dx.doi.org/10.1051/e3sconf/202126801007.
Повний текст джерелаДисертації з теми "Supervision signal"
Larsson, Emil. "Diagnosis and Supervision of Industrial Gas Turbines." Licentiate thesis, Linköpings universitet, Fordonssystem, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-75985.
Повний текст джерелаTayq, Zakaria. "Intégration et supervision des liens Fronthaul dans les réseaux 5G." Thesis, Limoges, 2017. http://www.theses.fr/2017LIMO0092/document.
Повний текст джерелаCloud Radio Access Network (RAN) was identified as a key enabler for 5G. Its deployment is however meeting multiple challenges notably in the fronthaul integration, the latter being the segment located between the Digital Unit and the Radio Unit generally based on CPRI. Giving its bit-rate, latency and jitter constrains, Wavelength Division Multiplexing (WDM) is the most adequate solution for its transport. However, the radio technologies recommended for 5G will drastically increase the CPRI bit-rate making its transport very challenging with low-cost WDM. This thesis deals with four main topics : The introduction of a control channel in the CPRI enables offering the WDM infrastructure monitoring and the wavelength tunability in the transceivers. The study of this control channel integration in the fronthaul link is reported in the second chapter as well as an investigation on the wireless transmission of CPRI. The use of Analog Radio over Fiber (A-RoF) can significantly improve the fronthaul spectral efficiency compared to CPRI-based fronthaul enabling, potentially, the transport of 5G interfaces. A thorough investigation on the actual gain brought by this solution is stated in the third chapter. CPRI compression based on uniform and non-uniform quantization is also a solution to enhance the CPRI spectral efficiency. The fourth chapter describes this solution and experimentally shows the achievable compression rates. Finally, establishing a new functional split in the radio equipment was considered as a promising solution for 5G. Two new interfaces have been identified for high and low layer functional splits. A theoretical and experimental study of these new interfaces is reported in the fifth chapter
Wacquet, Guillaume. "Classification spectrale semi-supervisée : Application à la supervision de l'écosystème marin." Thesis, Littoral, 2011. http://www.theses.fr/2011DUNK0389/document.
Повний текст джерелаIn the decision support systems, often, there a huge digital data and possibly some contextual knowledge available a priori or provided a posteriori by feedback. The performances of classification approaches, particularly spectral ones, depend on the integration of the domain knowledge in their design. Spectral classification algorithms address the problem of classification in terms of graph cuts. They classify the data in the eigenspace of the graph Laplacian matrix. The generated eigenspace may better reveal the presence of linearly separable data clusters. In this work, we are particularly interested in algorithms integrating pairwise constraints : constrained spectral clustering. The eigenspace may reveal the data structure while respecting the constraints. We present a state of the art approaches to constrained spectral clustering. We propose a new algorithm, which generates a subspace projection, by optimizing a criterion integrating both normalized multicut and penalties due to the constraints. The performances of the algorithms are demonstrated on different databases in comparison to other algorithms in the literature. As part of monitoring of the marine ecosystem, we developed a phytoplankton classification system, based on flow cytometric analysis. for this purpose, we proposed to characterize the phytoplanktonic cells by similarity measures using elastic comparison between their cytogram signals
Bechar, Hassane. "Comparaison d'images : Application à la surveillance et au suivi de trajectoire." Nancy 1, 1987. http://www.theses.fr/1987NAN10062.
Повний текст джерелаAl, Nazer Rouba. "Système de mesure d'impédance électrique embarqué, application aux batteries Li-ion." Phd thesis, Université de Grenoble, 2014. http://tel.archives-ouvertes.fr/tel-00958783.
Повний текст джерелаGamero, Argüello Fco Ignacio (Francisco Ignacio). "Pattern recognition based on qualitative representation of signals. Application to situation assessment of dynamic systems." Doctoral thesis, Universitat de Girona, 2012. http://hdl.handle.net/10803/83670.
Повний текст джерелаEl objetivo principal de la evaluación de situaciones es decidir sobre la adecuación del comportamiento del proceso con respecto a las especificaciones. Cuando no es posible tener un modelo matemático para representar el funcionamiento del sistema, otras técnicas deben considerarse. Los métodos de clasificación suelen ser propuestos como estrategias para el diagnóstico. La identificación de los estados funcionales se reduce a reconocer las formas de las variables como estados conocidos, comúnmente adquiriendo conocimiento de un experto o experiencias anteriores. Sin embargo, el conocimiento humano se relaciona con conceptos y símbolos, mientras que los sistemas de adquisición proporcionan datos numéricos. En consecuencia, este tipo de sistemas basados en el conocimiento de decisiones trabajan en un nivel superior de abstracción a través de representaciones simbólicas. Esta tesis aborda el estudio de métodos de clasificación de las tendencias cualitativas. El objetivo es clasificarlas por medio del conocimiento extraído de las experiencias pasadas.
Somon, Bertille. "Corrélats neuro-fonctionnels du phénomène de sortie de boucle : impacts sur le monitoring des performances." Thesis, Université Grenoble Alpes (ComUE), 2018. http://www.theses.fr/2018GREAS042/document.
Повний текст джерелаThe ongoing technological mutations occuring in aeronautics have profoundly changed the interactions between men and machines. Systems are more and more complex, automated and opaque. Several tragedies have reminded us that the supervision of those systems by human operators is still a challenge. Particularly, evidences have been made that automation has driven the operators away from the control loop of the system thus creating an out-of-the-loop phenomenon (OOL). This phenomenon is characterized by a decrease in situation awareness and vigilance, but also complacency and over-reliance towards automated systems. These difficulties have been shown to result in a degradation of the operator’s performances. Thus, the OOL phenomenon is a major issue of today’s society to improve human-machine interactions. Even though it has been studied for several decades, the OOL is still difficult to characterize, and even more to predict. The aim of this thesis is to define how cognitive neurosciences theories, such as the performance monitoring activity, can be used in order to better characterize the OOL phenomenon and the operator’s state, particularly through physiological measures. Consequently, we have used electroencephalographic activity (EEG) to try and identify markers and/or precursors of the supervision activity during system monitoring. In a first step we evaluated the error detection or performance monitoring activity through standard laboratory tasks, with varying levels of difficulty. We performed two EEG studies allowing us to show that : (i) the performance monitoring activity emerges both for our own errors detection but also during another agent supervision, may it be a human agent or an automated system, and (ii) the performance monitoring activity is significantly decreased by increasing task difficulty. These results led us to develop another experiment to assess the brain activity associated with system supervision in an ecological environment, resembling everydaylife aeronautical system monitoring. Thanks to adapted signal processing techniques (e.g. trial-by-trial time-frequency decomposition), we were able to show that there is : (i) a fronto-central θ activité time-locked to the system’s decision similar to the one obtained in laboratory condition, (ii) a decrease in overall supervision activity time-locked to the system’s decision, and (iii) a specific decrease of monitoring activity for errors. In this thesis, several EEG measures have been used in order to adapt to the context at hand. As a perspective, we have developped a final study aiming at defining the evolution of the monitoring activity during the OOL. Finding markers of this degradation would allow to monitor its emersion, and even better, predict it
Huamán, Aliaga Carlos Alberto Junior, and Chumpitaz Yameli Olenka Talla. "Desarrollo de un prototipo de supervisión médica, basado en IOT, para la detección de arritmia de tipo Fibrilación auricular en personas de la tercera edad en estado de reposo, mediante el monitoreo y procesamiento de señales ECG." Bachelor's thesis, Universidad Peruana de Ciencias Aplicadas (UPC), 2020. http://hdl.handle.net/10757/656502.
Повний текст джерелаThe present work proposes an electronic system for constant monitoring of the electrocardiographic signals of the patients for the detection of atrial fibrillation and sending the results in order to offer a complete medical supervision that expedites diagnosis and patient care. The system is composed of two parts, the first Hardware and the second Software. First, the system Hardware consists of equipment that allows electrocardiographic signals to be obtained, to process and send the signals to a database. Second, the system Software analyzes 02 parameters of the electrocardiographic signal to conclude if the patient has atrial fibrillation. The validation of the operation of the system is performed using signals from the Physionet database with 97.3% effectiveness and signals extracted from a sample of people with 85.7% effectiveness.
Tesis
Jiang-YongCheng and 承江永. "A Modified Time-Frequency Transform and Its Application to Power Quality Signal Supervision." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/y76822.
Повний текст джерела國立成功大學
電機工程學系
104
Continuous technological advancement has enabled conventional industries to upgrade into high-tech industries. The emphasis on the quality of supplying power has hence becomes more important than ever. Therefore, this study thoroughly investigated power supply quality signals by using an improved time-frequency transform method. This study first proposed Gabor-Wigner transform to investigate high impedance fault detection. In addition to being applicable to non-stationary signals, Gabor-Wigner transform exhibited major advantages such as considerably high time-frequency resolution and capability to overcome the noise problem in Wigner distribution. The method proposed in this dissertation was applied to high impedance fault detection in various situations, including on a cement ground, wet ground, and lawn. The experiment results revealed that this method can correctly detect high impedance faults in various conditions, serving as useful references for the study in the field of high impedance fault detection. Furthermore, the method proposed in this dissertation was applied to investigate various voltage flicker-generated signals such as 5Hz voltage flicker-generated signals, 10Hz voltage flicker-generated signals, voltage flicker-generated signals with harmonic signals, and the voltage flicker-generated signals produced by electric arc furnace operations. Test results of waveforms that were generated from simulations and measurements revealed that the proposed method effectively detected voltage flicker variations in all scenarios, benefiting engineers to grasp the quality information of power operations. The method proposed in this dissertation was also applied to discuss the inter-harmonic signals produced during the simulation and actual experiment. When analyzing the inter-harmonic signals in simulation, this method correctly detected the frequency and the time point of inter-harmonic signal occurrence, and the amplitude of each frequency. Moreover, when analyzing inter-harmonic signals of actual experiments, this method completed with a good detection without committing any misjudgment. Finally, the method proposed in this dissertation was used to investigate signals of voltage sag and voltage interruption as well. The results show that this method can identify the time point, frequency, and amplitude of power sags and interruptions. This method has also exhibited a higher resolution. The outcomes gained from these tests are useful for the improvement of electric power quality study.
Книги з теми "Supervision signal"
Luttrell, Stephen P. Self-supervision in multilayer adaptive networks. [London]: HMSO, 1991.
Знайти повний текст джерелаPollock, Steve. Coaching green belt projects for sustainable success. Milwaukee, Wisconsin: ASQ Quality Press, 2015.
Знайти повний текст джерелаChritton, M. R. Security system signal supervision. Supt. of Docs., U.S. G.P.O. [distributor], 1991.
Знайти повний текст джерелаSimon, Gleeson. Part VI Bank Group Supervision, 24 Group Supervision. Oxford University Press, 2018. http://dx.doi.org/10.1093/law/9780198793410.003.0024.
Повний текст джерелаWalters, Russell Craig. A distributed in-process supervision of milling based on signal processing machining models. 1993.
Знайти повний текст джерелаCorporation, National Learning. Supervisor (Signals). National Learning Corp, 2005.
Знайти повний текст джерелаCobb, William T. Digital filtering techniques for processing signals utilized in the unmanned supervision of machining. 1994.
Знайти повний текст джерелаLa citta senza nome: Segni e segnali nella metropoli moderna : Atti del 1o Convegno internazionale di studio sull'immagine della citta, Roma, 27-28 ottobre 1994 (Atti e documenti / Supervisione). Edizioni De Luca, 1996.
Знайти повний текст джерелаЧастини книг з теми "Supervision signal"
Dornfeld, D. "Signal Processing for Automatic Supervision." In Automatic Supervision in Manufacturing, 209–50. London: Springer London, 1994. http://dx.doi.org/10.1007/978-1-4471-3458-9_10.
Повний текст джерелаKe, Niu, Du Yihang, Niu Chenxu, and Li Panke. "Optimal Design of an Ecological Alarm Display for Automatic Train Supervision System." In Advances in Intelligent Information Hiding and Multimedia Signal Processing, 183–93. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-1053-1_17.
Повний текст джерелаBryant, Peter T. "Learning." In Augmented Humanity, 225–46. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-76445-6_8.
Повний текст джерелаBaqué, François, Olivier Descombin, Olivier Gastaldi, and Yves Vandenboomgaerde. "Aims, Context and Type of Signals Studied." In Supervision and Safety of Complex Systems, 183–90. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118561744.ch9.
Повний текст джерелаKebriaee, Javad, Hadi Chahkandi Nejad, and Sadegh Seynali. "Using an Active Learning Semi-supervision Algorithm for Classifying of ECG Signals and Diagnosing Heart Diseases." In Lecture Notes in Electrical Engineering, 69–82. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8672-4_6.
Повний текст джерелаPaś, Jacek, and Tomasz Klimczak. "Operational System Modelling in a Focused Fire Alarm System with an Open and Signal Detection Circuit Supervising Railway Station Premises." In Advances in Intelligent Systems and Computing, 307–16. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-27687-4_31.
Повний текст джерелаBarschdorff, D., P. M. Frank, R. Isermann, R. J. Patton, and D. Wach. "SIGNAL AND/OR MODEL BASED DIAGNOSIS." In Fault Detection, Supervision and Safety for Technical Processes 1991, 621. Elsevier, 1992. http://dx.doi.org/10.1016/b978-0-08-041275-7.50100-9.
Повний текст джерелаGustafsson, F. "Statistical Signal Processing Approaches to Fault Detection." In Fault Detection, Supervision and Safety of Technical Processes 2006, 24–35. Elsevier, 2007. http://dx.doi.org/10.1016/b978-008044485-7/50006-3.
Повний текст джерелаSamaan, M., M. Duque, and M. M'Saad. "A REAL TIME SUPERVISION SYSTEM FOR ADAPTIVE CONTROL." In Adaptive Systems in Control and Signal Processing 1989, 397–402. Elsevier, 1990. http://dx.doi.org/10.1016/b978-0-08-035727-0.50072-x.
Повний текст джерелаEndt, P., C. Rudolph, H. Schwetlick, and D. Filbert. "MULTI-LEVEL SIGNAL ABSTRACTION FOR DIAGNOSING ANALOGUE CIRCUITS." In Fault Detection, Supervision and Safety for Technical Processes 1991, 343–47. Elsevier, 1992. http://dx.doi.org/10.1016/b978-0-08-041275-7.50053-3.
Повний текст джерелаТези доповідей конференцій з теми "Supervision signal"
Jayawardana, Vindula, Anna Landler, and Cathy Wu. "Mixed Autonomous Supervision in Traffic Signal Control." In 2021 IEEE International Intelligent Transportation Systems Conference (ITSC). IEEE, 2021. http://dx.doi.org/10.1109/itsc48978.2021.9565053.
Повний текст джерелаOtero, A., P. Felix, F. Palacios, C. Perez-Gandia, and COS Sorzano. "Intelligent alarms for patient supervision." In 2007 IEEE International Symposium on Intelligent Signal Processing. IEEE, 2007. http://dx.doi.org/10.1109/wisp.2007.4447555.
Повний текст джерелаJin, Gaole, and Raviv Raich. "On surrogate supervision multiview learning." In 2012 IEEE International Workshop on Machine Learning for Signal Processing (MLSP). IEEE, 2012. http://dx.doi.org/10.1109/mlsp.2012.6349759.
Повний текст джерелаGfeller, Beat, Christian Frank, Dominik Roblek, Matt Sharifi, Marco Tagliasacchi, and Mihajlo Velimirovic. "Pitch Estimation Via Self-Supervision." In ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2020. http://dx.doi.org/10.1109/icassp40776.2020.9053798.
Повний текст джерелаMopuri, Konda Reddy, Vishal B. Athreya, and R. Venkatesh Babu. "Learning Representations with Strong Supervision for Image Search." In 2018 International Conference on Signal Processing and Communications (SPCOM). IEEE, 2018. http://dx.doi.org/10.1109/spcom.2018.8724475.
Повний текст джерелаHuan Zhang, Zheying Li, and Wenliang Niu. "Mine supervision system data analysis and transmission design." In 2008 9th International Conference on Signal Processing (ICSP 2008). IEEE, 2008. http://dx.doi.org/10.1109/icosp.2008.4697765.
Повний текст джерелаLi, Zhengxue, and Gaoyun An. "Human-Object Interaction Prediction with Natural Language Supervision." In 2022 16th IEEE International Conference on Signal Processing (ICSP). IEEE, 2022. http://dx.doi.org/10.1109/icsp56322.2022.9965210.
Повний текст джерелаLi, Bin, Xiaoguang Chen, Zhixin Wang, and Shulin Tan. "Vibration Signal Analysis For Rail Flaw Detection." In 2019 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS). IEEE, 2019. http://dx.doi.org/10.1109/safeprocess45799.2019.9213353.
Повний текст джерелаSalem, Sameh, and Asoke Nandi. "Novel Clustering Algorithm (RACAL) and a Partial Supervision Strategy for Classification." In 2006 16th IEEE Signal Processing Society Workshop on Machine Learning for Signal Processing. IEEE, 2006. http://dx.doi.org/10.1109/mlsp.2006.275567.
Повний текст джерелаYao, Tingting, Shenghua Dai, Pei Wang, and Yue He. "Image based obstacle detection for automatic train supervision." In 2012 5th International Congress on Image and Signal Processing (CISP). IEEE, 2012. http://dx.doi.org/10.1109/cisp.2012.6469703.
Повний текст джерелаЗвіти організацій з теми "Supervision signal"
Chritton, M. R., and J. C. Matter. Security system signal supervision. Office of Scientific and Technical Information (OSTI), September 1991. http://dx.doi.org/10.2172/6276408.
Повний текст джерелаLópez Boo, Florencia, María de la Paz Ferro, and Pedro Carneiro. ¿Funciona integrar servicios de primera infancia con los servicios de salud?: Evidencia experimental del programa de visitas domiciliarias Cresça Com Seu Filho. Inter-American Development Bank, April 2021. http://dx.doi.org/10.18235/0003230.
Повний текст джерела