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Erschienen in:
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2019 | OriginalPaper | Buchkapitel

1. Hybrid Intelligent Networks

verfasst von : Zhi-Hong Guan, Bin Hu, Xuemin (Sherman) Shen

Erschienen in: Introduction to Hybrid Intelligent Networks

Verlag: Springer International Publishing

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Abstract

In this chapter, a broad but self-contained overview of the terminology of hybrid intelligent network is provided. Section 1.1 first presents a typical hybrid intelligent network, the human brain. It is the brain science and brain-inspired intelligence that motivate the study of hybrid intelligent networks in this book. Section 1.2 generally introduces nonlinear phenomena in nature and engineering, and the hybrid nonlinearity and hybrid intelligence are highlighted. The hybrid intelligent network models are discussed in Sect. 1.3, including hybrid dynamical systems, complex networks, and artificial neural networks. Section 1.4 proposes the basic concepts and methodologies in the field of hybrid intelligent networks that are widely used in for the subsequent chapters. Section 1.5 sketches the overall organization of the book where each chapter is briefly summarized for an overview of the book. Section 1.6 concludes the chapter.

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Nächstes Kapitel Delayed Hybrid Impulsive Neural Networks
Fußnoten
1
Hybrid control involves both continuous-time evolution and discrete-time jumps. Please note that the definition of hybrid control is unspecific.
 
2
Hebbian theory [4].
 
3
For more information, interested readers may refer to [11‐13].
 
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B. Hu, Z.-H. Guan, T.-H. Qian, and G. Chen, “Dynamic analysis of hybrid impulsive delayed neural networks with uncertainties,” IEEE Trans. Neural Networks and Learning Systems, vol. 29, no. 9, pp. 4370–4384, 2018.CrossRef
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B. Hu, Z.-H. Guan, G. Chen, and F. L. Lewis, “Multistability of delayed hybrid impulsive neural networks with application to associative memories,” IEEE Trans. Neural Networks and Learning Systems, In Press, DOI: 10.1109/TNNLS.2018.2870553, 2018.
19.
B. Hu, Z.-H. Guan, N. Xiong, and H.-C. Chao, “Intelligent impulsive synchronization of nonlinear interconnected neural networks for image protection,” IEEE Trans. Industrial Informatics, vol. 14, no. 8, pp. 3775–3787, 2018.CrossRef
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23.
Z.-H. Guan, B. Hu, M. Chi, D.-X. He, and X.-M. Cheng, “Guaranteed performance consensus in second-order multi-agent systems with hybrid impulsive control,” Automatica, vol. 50, no. 9, pp. 2415–2418, 2014.MathSciNetCrossRef
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25.
B. Hu, Z.-H. Guan, X.-W. Jiang, R.-Q. Liao, and C.-Y. Chen, “Event-driven multi-consensus of multi-agent networks with repulsive links,” Inf. Sciences, vol. 373, pp. 110–123, 2016.CrossRef
26.
B. Hu, Z.-H. Guan, G. Chen, and X. Shen, “A distributed hybrid event-time-driven scheme for optimization over sensor networks,” IEEE Trans. Industrial Electronics, In Press, DOI: 10.1109/TIE.2018.2873517, 2018.
Metadaten
Titel
Hybrid Intelligent Networks
verfasst von
Zhi-Hong Guan
Bin Hu
Xuemin (Sherman) Shen
Copyright-Jahr
2019
Buch
Introduction to Hybrid Intelligent Networks

Print ISBN: 978-3-030-02160-3

Electronic ISBN: 978-3-030-02161-0

Copyright-Jahr: 2019

DOI
https://doi.org/10.1007/978-3-030-02161-0_1

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