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Статті в журналах з теми "Gated Continuous Logic Networks"
Boukadida, Souha, Soufien Gdaim, and Abdellatif Mtiba. "Sensor Fault Detection and Isolation Based on Artificial Neural Networks and Fuzzy Logic Applicated on Induction Motor for Electrical Vehicle." International Journal of Power Electronics and Drive Systems (IJPEDS) 8, no. 2 (June 1, 2017): 601. http://dx.doi.org/10.11591/ijpeds.v8.i2.pp601-611.
Повний текст джерелаTran, Duc M., Kyungah Kim, and Joon-Young Choi. "CLB-Based Development of BiSS-C Interface Master for Motor Encoders." Electronics 12, no. 4 (February 9, 2023): 886. http://dx.doi.org/10.3390/electronics12040886.
Повний текст джерелаKIROLOS, SAMI, and YEHIA MASSOUD. "DYNAMIC VOLTAGE SCALING CONTINUOUS ADAPTIVE-SIZE CELL DESIGN TECHNIQUE." Journal of Circuits, Systems and Computers 17, no. 05 (October 2008): 871–83. http://dx.doi.org/10.1142/s0218126608004630.
Повний текст джерелаPlyusnin, Nikolay. "Tunable logic of complex variables and quantum networks on its basis." Robotics and Technical Cybernetics 10, no. 4 (December 2022): 267–74. http://dx.doi.org/10.31776/rtcj.10404.
Повний текст джерелаLi, Zhitao, Yuqian Guo, and Weihua Gui. "Asymptotical feedback controllability of continuous-time probabilistic logic control networks." Nonlinear Analysis: Hybrid Systems 47 (February 2023): 101265. http://dx.doi.org/10.1016/j.nahs.2022.101265.
Повний текст джерелаYadav, Neetika, Neeta Pandey, and Deva Nand. "Leakage reduction in dual mode logic through gated leakage transistors." Microprocessors and Microsystems 84 (July 2021): 104269. http://dx.doi.org/10.1016/j.micpro.2021.104269.
Повний текст джерелаChen, Lanlan. "Secure Data Sequence Recognition of All-Optical High-Speed Network Using Semiconductor Optical Amplifier." Journal of Nanoelectronics and Optoelectronics 16, no. 10 (October 1, 2021): 1667–74. http://dx.doi.org/10.1166/jno.2021.3124.
Повний текст джерелаBuckley, J. J., and Yoichi Hayashi. "Numerical relationships between neural networks, continuous functions, and fuzzy systems." Fuzzy Sets and Systems 60, no. 1 (November 1993): 1–8. http://dx.doi.org/10.1016/0165-0114(93)90283-n.
Повний текст джерелаCsiszár, Orsolya, Gábor Csiszár, and József Dombi. "Interpretable neural networks based on continuous-valued logic and multicriteria decision operators." Knowledge-Based Systems 199 (July 2020): 105972. http://dx.doi.org/10.1016/j.knosys.2020.105972.
Повний текст джерелаSturlaugson, Liessman, Logan Perreault, and John W. Sheppard. "Factored performance functions and decision making in continuous time Bayesian networks." Journal of Applied Logic 22 (July 2017): 28–45. http://dx.doi.org/10.1016/j.jal.2016.11.030.
Повний текст джерелаДисертації з теми "Gated Continuous Logic Networks"
Habib, Carol. "Energy-efficient data collection and fusion in wireless body sensor networks for continuous health monitoring." Thesis, Bourgogne Franche-Comté, 2018. http://www.theses.fr/2018UBFCD046.
Повний текст джерелаSeveral challenges exist in Wireless Body Sensor Networks such as the data collection and fusion especially that (1) wireless sensor nodes have limited energy, processing and memory resources, (2) the amount of periodically gathered data is huge, (3) the gathered data are characterized by a heterogeneous nature and (4) the data interpretation to ensure decision-support is influenced byseveral external factors such as the provided context information of the monitored person.In this thesis, the aforementioned challenges were tackled by proposing scientific aproaches. Firstly, an energy-efficient data collection technique is proposed. This technique targets the energy consumed by biosensor nodes for sensing and transmitting vital signs. It consists of a real-timesampling rate adaptation mechanism and a local detection system which are provided at the level of the nodes. Second, in order to perform a health assessment based on the collected data, a multisensor data fusion model is proposed. In this approach, the coordinator of the network performs anassessment of the patient's health condition based on the collected measurements of his/her vital signs. Such data is interpreted in a human-reasoning way and are characterized by ambiguity and imprecision. Thus, we propose to use a Fuzzy Inference System. Then, given that vital signs are highly correlated to the context of the monitored person, a context-aware multi-sensor data fusionmodel for health assessment is proposed. The person's context include his/her physical activity status, medical record and personal information. This information highly influences the interpretation of vital signs. Hesitant fuzzy sets are used to subjectively evaluate the intensity of the person's physical activities based on his/her personal information and the activity's characteristics. Finally, a specific healthcare monitoring application is targeted. A real-time stress detection and evaluation framework is proposed while taking into consideration the energy consumption constraint. Shimmer 3 GSR+ is used as a wireless sensor node to sense the Photoplethysmogram (PPG) signal and the skin conductance. An android mobile application is developed to extract from the PPG signal stress correlated vital signs such as the heart rate, the respiration rate and the blood pressure
Behaegel, Jonathan. "Modèles hybrides de réseaux de régulation : étude du couplage des cycles cellulaire et circadien." Thesis, Université Côte d'Azur (ComUE), 2018. http://www.theses.fr/2018AZUR4071/document.
Повний текст джерелаModelling biological systems has become instrumental to understand complex and emerging phenomena resulting from partially known influences, and to consider controlling an altered system in order to restore a physiological behaviour. Any model, independent of the underlying paradigm, involves parameters governing its dynamics. However, experimental measurements generally do not allow their identification and this remains one of the major problems of modelling. This PhD proposes an automatic method for identifying the dynamic parameters of biological systems in a hybrid modelling framework. The chosen hybrid framework splits the phase space according to the activity of the biological entities, and associates to each of these subspaces a celerity for each of the components. We introduce a continuous time Hoare logic as well as its weakest precondition calculus which, from qualitative and chronometrical experimental observations, constructs the minimum constraints on the model parameters making it compatible with the observations. This calculus leads to a Constraint Satisfaction Problem on real numbers and we show that it can be solved by the AbSolute solver.The Holmes BioNet prototype developed during this PhD can not only automate the parameter identification process from experimental data, but also simulate the evolution of the obtained model in order to compare it with experimental traces. We use this prototype to model the coupling of the cellular and circadian cycles
Dalecký, Štěpán. "Neuro-fuzzy systémy." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2014. http://www.nusl.cz/ntk/nusl-236066.
Повний текст джерелаRaja, Ravi. "Boolean Functional Synthesis using Gated Continuous Logic Networks." Thesis, 2022. https://etd.iisc.ac.in/handle/2005/5918.
Повний текст джерелаЧастини книг з теми "Gated Continuous Logic Networks"
Li, Xiaolin. "The Classical Logic and the Continuous Logic." In Lecture Notes in Networks and Systems, 511–25. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-18461-1_33.
Повний текст джерелаCarreon-Ortiz, Hector, Fevrier Valdez, and Oscar Castillo. "A New Continuous Mycorrhiza Optimization Nature-Inspired Algorithm." In Hybrid Intelligent Systems Based on Extensions of Fuzzy Logic, Neural Networks and Metaheuristics, 147–64. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-28999-6_10.
Повний текст джерелаDombi, József, and Orsolya Csiszár. "Interpretable Neural Networks Based on Continuous-Valued Logic and Multi-criteria Decision Operators." In Explainable Neural Networks Based on Fuzzy Logic and Multi-criteria Decision Tools, 147–69. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72280-7_9.
Повний текст джерелаGarcía-Morales, Miguel Á., Héctor J. Fraire-Huacuja, José A. Brambila-Hernández, Juan Frausto-Solís, Laura Cruz-Reyes, Claudia G. Gómez-Santillán, and Juan M. Carpio-Valadez. "Particle Swarm Optimization Algorithm with Improved Opposition-Based Learning (IOBL-PSO) to Solve Continuous Problems." In Hybrid Intelligent Systems Based on Extensions of Fuzzy Logic, Neural Networks and Metaheuristics, 115–26. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-28999-6_7.
Повний текст джерелаBobed, Carlos, Fernando Bobillo, Sergio Ilarri, and Eduardo Mena. "Answering Continuous Description Logic Queries." In Mobile Computing and Wireless Networks, 893–938. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-8751-6.ch039.
Повний текст джерелаTrappenberg, Thomas P. "Recurrent associative networks and episodic memory." In Fundamentals of Computational Neuroscience, 250–300. 3rd ed. Oxford University PressOxford, 2022. http://dx.doi.org/10.1093/oso/9780192869364.003.0009.
Повний текст джерелаDasso, Aristides, and Ana Funes. "Threat and Risk Assessment Using Continuous Logic." In Research Anthology on Business Aspects of Cybersecurity, 156–72. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-3698-1.ch007.
Повний текст джерелаDasso, Aristides, and Ana Funes. "Threat and Risk Assessment Using Continuous Logic." In Encyclopedia of Organizational Knowledge, Administration, and Technology, 1212–27. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-3473-1.ch083.
Повний текст джерелаPreto, Sandro, and Marcelo Finger. "Chapter 28. Effective Reasoning over Neural Networks Using Łukasiewicz Logic." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2023. http://dx.doi.org/10.3233/faia230160.
Повний текст джерелаPatino, Luis, André Constantinesco, and Ernest Hirsch. "Contouring Blood Pool Myocardial Gated SPECT Images with a Sequence of Three Techniques Based on Wavelets, Neural Networks, and Fuzzy Logic." In FUZZY and NEURO-FUZZY SYSTEMS in MEDICINE, 95–136. CRC Press, 2017. http://dx.doi.org/10.1201/9780203713419-5.
Повний текст джерелаТези доповідей конференцій з теми "Gated Continuous Logic Networks"
Yao, Jianan, Gabriel Ryan, Justin Wong, Suman Jana, and Ronghui Gu. "Learning nonlinear loop invariants with gated continuous logic networks." In PLDI '20: 41st ACM SIGPLAN International Conference on Programming Language Design and Implementation. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3385412.3385986.
Повний текст джерелаKrestinskaya, O., and A. P. James. "Approximate Probabilistic Neural Networks with Gated Threshold Logic." In 2018 IEEE 18th International Conference on Nanotechnology (IEEE-NANO). IEEE, 2018. http://dx.doi.org/10.1109/nano.2018.8626302.
Повний текст джерелаNguyen, Van Thien, William Guicquero, and Gilles Sicard. "Histogram-Equalized Quantization for logic-gated Residual Neural Networks." In 2022 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE, 2022. http://dx.doi.org/10.1109/iscas48785.2022.9937290.
Повний текст джерелаHeinrich, Stefan, Tayfun Alpay, and Yukie Nagai. "Learning Timescales in Gated and Adaptive Continuous Time Recurrent Neural Networks." In 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE, 2020. http://dx.doi.org/10.1109/smc42975.2020.9282864.
Повний текст джерелаGupta, Nidhi. "Clock Power Analysis of Low Power Clock Gated Arithmetic Logic Unit on Different FPGA." In 2014 International Conference on Computational Intelligence and Communication Networks (CICN). IEEE, 2014. http://dx.doi.org/10.1109/cicn.2014.192.
Повний текст джерелаLi, Zhitao, Yuqian Guo, and Weihua Gui. "Asymptotical Feedback Controllability of Continuous-time Probabilistic Logic Control Networks." In 2020 IEEE 16th International Conference on Control & Automation (ICCA). IEEE, 2020. http://dx.doi.org/10.1109/icca51439.2020.9264501.
Повний текст джерелаShrivastava, Gunjan, and Shivendra Singh. "Power Optimization of Sequential Circuit Based ALU Using Gated Clock & Pulse Enable Logic." In 2014 International Conference on Computational Intelligence and Communication Networks (CICN). IEEE, 2014. http://dx.doi.org/10.1109/cicn.2014.212.
Повний текст джерелаZhang, Wei, Yongxiang Liu, Zhuo Wang, and Jianyong Wang. "Learning to Binarize Continuous Features for Neuro-Rule Networks." In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. California: International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/510.
Повний текст джерелаKrasilenko, Vladimir G., Oleg K. Kolesnitsky, and Anatoly K. Bogukhvalsky. "Creation opportunities for optoelectronic continuous logic neural elements which are the universal circuitry macrobasis of optical neural networks." In International Conference on Holography and Correlation Optics, edited by Oleg V. Angelsky. SPIE, 1995. http://dx.doi.org/10.1117/12.226696.
Повний текст джерелаFlaminio, Tommaso, Sandro Preto, and Sara Ugolini. "Reasoning about Probability via Continuous Functions." In 20th International Conference on Principles of Knowledge Representation and Reasoning {KR-2023}. California: International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/kr.2023/28.
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