Libri sul tema "Network based control systems"

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1

Liu, G. P. Neural network based predictive control for nonlinear systems. Sheffield: University of Sheffield, Dept. of Automatic Control and Systems Engineering, 1996.

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2

Esfandiari, Kasra, Farzaneh Abdollahi e Heidar A. Talebi. Neural Network-Based Adaptive Control of Uncertain Nonlinear Systems. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-73136-6.

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3

Zhao, Yun-Bo, Guo-Ping Liu, Yu Kang e Li Yu. Packet-Based Control for Networked Control Systems. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-6250-6.

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4

Liu, G. P. Neural network based variable structure control for nonlinear discrete systems. Sheffield: University of Sheffield, Dept. of Automatic Control and Systems Engineering, 1996.

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5

Garcia, Eloy, Panos J. Antsaklis e Luis A. Montestruque. Model-Based Control of Networked Systems. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07803-8.

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6

Mazumder, Sudip K. Wireless Networking Based Control. New York, NY: Springer Science+Business Media, LLC, 2011.

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7

Joby, P. P., Valentina E. Balas e Ram Palanisamy, a cura di. IoT Based Control Networks and Intelligent Systems. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-5845-8.

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8

Joby, P. P., Marcelo S. Alencar e Przemyslaw Falkowski-Gilski, a cura di. IoT Based Control Networks and Intelligent Systems. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-6586-1.

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9

Elli, Kartsakli, a cura di. Contention-based collision-resolution medium access control algorithms. New York: Nova Science Publishers, 2009.

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10

Elli, Kartsakli, a cura di. Contention-based collision-resolution medium access control algorithms. New York: Nova Science Publishers, 2009.

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11

Hassan, Sabo Miya, Rosdiazli Ibrahim, Nordin Saad, Kishore Bingi e Vijanth Sagayan Asirvadam. Hybrid PID Based Predictive Control Strategies for WirelessHART Networked Control Systems. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-47737-0.

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12

Zou, Lei, Zidong Wang e Jinling Liang. Communication-Protocol-Based Filtering and Control of Networked Systems. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-97512-8.

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13

Teshnehlab, Mohammad. Intelligent Control Based on Flexible Neural Networks. Dordrecht: Springer Netherlands, 1999.

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14

Teshnehlab, Mohammad. Intelligent control based on flexible neural networks. Dordrecht: Kluwer Academic Publishers, 1999.

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15

Ning, Peng. Intrusion Detection in Distributed Systems: An Abstraction-Based Approach. Boston, MA: Springer US, 2004.

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16

Talebi, H. A. Neural network-based state estimation of nonlinear systems: Application to fault detection and isolation. New York: Springer, 2010.

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17

D, Ivancic William, Kim Heechul e United States. National Aeronautics and Space Administration., a cura di. On-board closed-loop congestion control for satellite based packet switching networks. [Washington, DC]: National Aeronautics and Space Administration, 1993.

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18

D, Ivancic William, Kim Heechul e United States. National Aeronautics and Space Administration., a cura di. On-board closed-loop congestion control for satellite based packet switching networks. [Washington, DC]: National Aeronautics and Space Administration, 1993.

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19

Elia, Alberto. Human-machine interface design for process control safety profiles for real-time ethernet-based industrial automation networks. Research Triangle Park, NC: Instrumentation, Systems, and Automation Society, 2009.

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20

Lassa, Jonatan Anderias. Conceptualizing an established network of a community based flood early warning system: Case of Cawang, East Jakarta, Jakarta, Indonesia. [Kupang, NTT, Indonesia]: IRGSC, 2013.

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21

Yŏnʼguwŏn, Hanʼguk Chŏnja Tʻongsin, a cura di. Tibaisŭ injŭng kiban ŭi yubikʻwŏtʻŏsŭ hom netʻŭwŏkʻŭ poan kisul kaebal =: The development of security technology based on device authentication for ubiquitous home network. [Seoul]: Chisik Kyŏngjebu, 2008.

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22

Heuberger, Albert. Microelectronic Systems: Circuits, Systems and Applications. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2011.

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23

Milford, Michael John. Robot navigation from nature: Simultaneous localisation, mapping, and path planning based on hippocampal models. Berlin: Springer, 2008.

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24

Ning, Peng. Intrusion detection in distributed systems: An abstraction-based approach. Boston: Kluwer Academic Publishers, 2004.

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25

Varlamov, Oleg. Fundamentals of creating MIVAR expert systems. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1513119.

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Abstract (sommario):
Methodological and applied issues of the basics of creating knowledge bases and expert systems of logical artificial intelligence are considered. The software package "MIV Expert Systems Designer" (KESMI) Wi!Mi RAZUMATOR" (version 2.1), which is a convenient tool for the development of intelligent information systems. Examples of creating mivar expert systems and several laboratory works are given. The reader, having studied this tutorial, will be able to independently create expert systems based on KESMI. The textbook in the field of training "Computer Science and Computer Engineering" is intended for students, bachelors, undergraduates, postgraduates studying artificial intelligence methods used in information processing and management systems, as well as for users and specialists who create mivar knowledge models, expert systems, automated control systems and decision support systems. Keywords: cybernetics, artificial intelligence, mivar, mivar networks, databases, data models, expert system, intelligent systems, multidimensional open epistemological active network, MOGAN, MIPRA, KESMI, Wi!Mi, Razumator, knowledge bases, knowledge graphs, knowledge networks, Big knowledge, products, logical inference, decision support systems, decision-making systems, autonomous robots, recommendation systems, universal knowledge tools, expert system designers, logical artificial intelligence.
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26

Patil, Harsh Kupwade. Security for wireless sensor networks using identity-based cryptography. Boca Raton: CRC Press/Taylor & Francis Group, 2013.

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27

Enokido, Tomoya, Leonard Barolli e Makoto Takizawa, a cura di. Network-Based Information Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-74573-0.

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28

Takizawa, Makoto, Leonard Barolli e Tomoya Enokido, a cura di. Network-Based Information Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-85693-1.

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29

Kormanyos, Christopher Michael. Real-time C++: Efficient object-oriented and template micro-controller programming. Heidelberg: Springer, 2013.

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30

Guang-Zhong, Yang, a cura di. Body sensor networks. London: Springer, 2006.

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31

International Conference on Knowledge-Based Intelligent Electronic Systems (2nd 1998 Adelaide, South Australia). 1998 second International Conference on Knowledge-Based Intelligent Electronic Systems: Proceedings : KES '98 : Adelaide, South Australia, 21-23 April, 1998. A cura di Jain L. C, Jain R. K e Institute of Electrical and Electronics Engineers. Piscataway, New Jersey: IEEE, 1998.

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32

International Conference on Knowledge-Based Intelligent Information and Engineering Systems (14th 2010 Cardiff, Wales). Knowledge-based and intelligent information and engineering systems: 14th international conference, KES 2010, Cardiff, UK, September 8-10, 2010 : proceedings. Berlin: Springer, 2010.

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33

International Conference on Knowledge-Based Intelligent Information Engineering Systems (3rd 1999 Adelaide, South Australia). 1999 third International Conference on Knowledge-Based Intelligent Information Engineering Systems: Proceedings : KES '99 : Adelaide, South Australia, 31 August-1 September 1999. A cura di Jain L. C, Institute of Electrical and Electronics Engineers. e International Conference on Knowledge-Based Intelligent Electronic Systems. Piscataway, New Jersey: IEEE, 1999.

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34

Schall, Daniel. Social Network-Based Recommender Systems. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-22735-1.

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35

Sinha, Naresh K., a cura di. Microprocessor-Based Control Systems. Dordrecht: Springer Netherlands, 1986. http://dx.doi.org/10.1007/978-94-009-4708-5.

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36

Yang, Shuang-Hua. Internet-based Control Systems. London: Springer London, 2011. http://dx.doi.org/10.1007/978-1-84996-359-6.

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37

1927-, Sinha N. K., a cura di. Microprocessor-based control systems. Dordrecht: D. Reidel Pub. Co., 1986.

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38

Sinha, Naresh K. Microprocessor-Based Control Systems. Dordrecht: Springer Netherlands, 1986.

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39

International Conference on Knowledge-Based Intelligent Information and Engineering Systems (11th 2007 Vietri sul Mare, Italy). Knowledge-based intelligent information and engineering systems: KES 2007 - WIRN 2007: 11th international conference, KES 2007, XVII Italian Workshop on Neural Networks, Vietri sul Mare, Italy, September 12-14, 2007 ; proceedings. Berlin: Springer, 2007.

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40

Varlamov, Oleg. Mivar databases and rules. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1508665.

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Abstract (sommario):
The multidimensional open epistemological active network MOGAN is the basis for the transition to a qualitatively new level of creating logical artificial intelligence. Mivar databases and rules became the foundation for the creation of MOGAN. The results of the analysis and generalization of data representation structures of various data models are presented: from relational to "Entity — Relationship" (ER-model). On the basis of this generalization, a new model of data and rules is created: the mivar information space "Thing-Property-Relation". The logic-computational processing of data in this new model of data and rules is shown, which has linear computational complexity relative to the number of rules. MOGAN is a development of Rule - Based Systems and allows you to quickly and easily design algorithms and work with logical reasoning in the "If..., Then..." format. An example of creating a mivar expert system for solving problems in the model area "Geometry"is given. Mivar databases and rules can be used to model cause-and-effect relationships in different subject areas and to create knowledge bases of new-generation applied artificial intelligence systems and real-time mivar expert systems with the transition to"Big Knowledge". The textbook in the field of training "Computer Science and Computer Engineering" is intended for students, bachelors, undergraduates, postgraduates studying artificial intelligence methods used in information processing and management systems, as well as for users and specialists who create mivar knowledge models, expert systems, automated control systems and decision support systems. Keywords: cybernetics, artificial intelligence, mivar, mivar networks, databases, data models, expert system, intelligent systems, multidimensional open epistemological active network, MOGAN, MIPRA, KESMI, Wi!Mi, Razumator, knowledge bases, knowledge graphs, knowledge networks, Big knowledge, products, logical inference, decision support systems, decision-making systems, autonomous robots, recommendation systems, universal knowledge tools, expert system designers, logical artificial intelligence.
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41

Esfandiari, Kasra, Farzaneh Abdollahi e Heidar A. Talebi. Neural Network-Based Adaptive Control of Uncertain Nonlinear Systems. Springer International Publishing AG, 2022.

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42

Esfandiari, Kasra, Farzaneh Abdollahi e Heidar A. Talebi. Neural Network-Based Adaptive Control of Uncertain Nonlinear Systems. Springer International Publishing AG, 2021.

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43

Model-based control of networked systems. Birkhäuser, 2014.

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44

Antsaklis, Panos J., Eloy Garcia e Luis A. Montestruque. Model-Based Control of Networked Systems. Birkhauser Verlag, 2014.

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45

Antsaklis, Panos J., Eloy Garcia e Luis A. Montestruque. Model-Based Control of Networked Systems. Birkhäuser Boston, 2016.

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46

Mazumder, Sudip K. Wireless Networking Based Control. Springer, 2014.

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47

Mazumder, Sudip K. Wireless Networking Based Control. Springer, 2011.

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48

Fischer, Joerg. Optimal Sequence-Based Control of Networked Linear Systems. Karlsruhe Scientific Publishing, 2015.

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49

Fischer, Jörg. Optimal Sequence-Based Control of Networked Linear Systems. Saint Philip Street Press, 2020.

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50

Baily, Albert L. Multi-media presentation system based on a distributed control network. 1991.

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