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Introduction to hybrid intelligent n...

Guan, Zhi-Hong.

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Introduction to hybrid intelligent networks = modeling, communication, and control /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Introduction to hybrid intelligent networks/ by Zhi-Hong Guan, Bin Hu, Xuemin (Sherman) Shen.
其他題名:	modeling, communication, and control /
作者:	Guan, Zhi-Hong.
其他作者:	Hu, Bin.
出版者:	Cham :Springer International Publishing : : 2019.,
面頁冊數:	ix, 292 p. :ill. (some col.), digital ;24 cm.
內容註:	1 Hybrid Intelligent Networks -- 2 Delayed Hybrid Impulsive Neural Networks -- 3 Hybrid Impulsive Neural Networks with Interval-Uncertain Weights -- 4 Multistability of Hybrid Impulsive Neural Networks and Associative Memories -- 5 Impulsive Neural Networks Towards Image Protection -- 6 Hybrid Memristor-Based Impulsive Neural Networks -- 7 Hybrid Impulsive and Switching Control -- 8 Hybrid Communication and Control in Multi-Agent Networks -- 9 Event-Driven Communication and Control in Multi-Agent Networks -- 10 Hybrid Event-Time-Driven Communication and Network Optimization.
Contained By:	Springer eBooks
標題:	Intelligent agents (Computer software) -
電子資源:	https://doi.org/10.1007/978-3-030-02161-0
ISBN:	9783030021610

Introduction to hybrid intelligent networks = modeling, communication, and control /
Guan, Zhi-Hong.

Introduction to hybrid intelligent networksmodeling, communication, and control /[electronic resource] :by Zhi-Hong Guan, Bin Hu, Xuemin (Sherman) Shen. - Cham :Springer International Publishing :2019. - ix, 292 p. :ill. (some col.), digital ;24 cm.

1 Hybrid Intelligent Networks -- 2 Delayed Hybrid Impulsive Neural Networks -- 3 Hybrid Impulsive Neural Networks with Interval-Uncertain Weights -- 4 Multistability of Hybrid Impulsive Neural Networks and Associative Memories -- 5 Impulsive Neural Networks Towards Image Protection -- 6 Hybrid Memristor-Based Impulsive Neural Networks -- 7 Hybrid Impulsive and Switching Control -- 8 Hybrid Communication and Control in Multi-Agent Networks -- 9 Event-Driven Communication and Control in Multi-Agent Networks -- 10 Hybrid Event-Time-Driven Communication and Network Optimization.

This book covers the fundamental principles, new theories and methodologies, and potential applications of hybrid intelligent networks. Chapters focus on hybrid neural networks and networked multi-agent networks, including their communication, control and optimization synthesis. This text also provides a succinct but useful guideline for designing neural network-based hybrid artificial intelligence for brain-inspired computation systems and applications in the Internet of Things. Artificial Intelligence has developed into a deep research field targeting robots with more brain-inspired perception, learning, decision-making abilities, etc. This text devoted to a tutorial on hybrid intelligent networks that have been identified in nature and engineering, especially in the brain, modeled by hybrid dynamical systems and complex networks, and have shown potential application to brain-inspired intelligence. Included in this text are impulsive neural networks, neurodynamics, multiagent networks, hybrid dynamics analysis, collective dynamics, as well as hybrid communication, control and optimization methods. Graduate students who are interested in artificial intelligence and hybrid intelligence, as well as professors and graduate students who are interested in neural networks and multiagent networks will find this textbook a valuable resource. AI engineers and consultants who are working in wireless communications and networking will want to buy this book. Also, professional and academic institutions in universities and Mobile vehicle companies and engineers and managers who concern humans in the loop of IoT will also be interested in this book.

ISBN: 9783030021610

Standard No.: 10.1007/978-3-030-02161-0doiSubjects--Topical Terms:

567546
Intelligent agents (Computer software)

LC Class. No.: QA76.76.I58

Dewey Class. No.: 006.30285436

Introduction to hybrid intelligent networks = modeling, communication, and control /
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520 $a This book covers the fundamental principles, new theories and methodologies, and potential applications of hybrid intelligent networks. Chapters focus on hybrid neural networks and networked multi-agent networks, including their communication, control and optimization synthesis. This text also provides a succinct but useful guideline for designing neural network-based hybrid artificial intelligence for brain-inspired computation systems and applications in the Internet of Things. Artificial Intelligence has developed into a deep research field targeting robots with more brain-inspired perception, learning, decision-making abilities, etc. This text devoted to a tutorial on hybrid intelligent networks that have been identified in nature and engineering, especially in the brain, modeled by hybrid dynamical systems and complex networks, and have shown potential application to brain-inspired intelligence. Included in this text are impulsive neural networks, neurodynamics, multiagent networks, hybrid dynamics analysis, collective dynamics, as well as hybrid communication, control and optimization methods. Graduate students who are interested in artificial intelligence and hybrid intelligence, as well as professors and graduate students who are interested in neural networks and multiagent networks will find this textbook a valuable resource. AI engineers and consultants who are working in wireless communications and networking will want to buy this book. Also, professional and academic institutions in universities and Mobile vehicle companies and engineers and managers who concern humans in the loop of IoT will also be interested in this book.
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