Higher Order Networks

Author : Ginestra Bianconi
Publisher : Cambridge University Press
ISBN 13 : 1108726739
Total Pages : 149 pages
Book Rating : 4.33/5 ( download)

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Download or read book Higher Order Networks: An Introduction to Simplicial Complexes written by Ginestra Bianconi and published by Cambridge University Press. This book was released on 2021-12-23 with total page 149 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Element presents one of the most recent developments in network science in a highly accessible style. This Element will be of interest to interdisciplinary scientists working in network science, in addition to mathematicians working in discrete topology and geometry and physicists working in quantum gravity.

Author : Zhang, Ming
Publisher : IGI Global
ISBN 13 : 1466621761
Total Pages : 455 pages
Book Rating : 4.63/5 ( download)

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Download or read book Artificial Higher Order Neural Networks for Modeling and Simulation written by Zhang, Ming and published by IGI Global. This book was released on 2012-10-31 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book introduces Higher Order Neural Networks (HONNs) to computer scientists and computer engineers as an open box neural networks tool when compared to traditional artificial neural networks"--Provided by publisher.

Author : Zhang, Ming
Publisher : IGI Global
ISBN 13 : 1615207120
Total Pages : 660 pages
Book Rating : 4.21/5 ( download)

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Download or read book Artificial Higher Order Neural Networks for Computer Science and Engineering: Trends for Emerging Applications written by Zhang, Ming and published by IGI Global. This book was released on 2010-02-28 with total page 660 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book introduces and explains Higher Order Neural Networks (HONNs) to people working in the fields of computer science and computer engineering, and how to use HONNS in these areas"--Provided by publisher.

Author : Jan Treur
Publisher : Springer Nature
ISBN 13 : 3030314456
Total Pages : 412 pages
Book Rating : 4.53/5 ( download)

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Download or read book Network-Oriented Modeling for Adaptive Networks: Designing Higher-Order Adaptive Biological, Mental and Social Network Models written by Jan Treur and published by Springer Nature. This book was released on 2019-11-01 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses the challenging topic of modeling adaptive networks, which often manifest inherently complex behavior. Networks by themselves can usually be modeled using a neat, declarative, and conceptually transparent Network-Oriented Modeling approach. In contrast, adaptive networks are networks that change their structure; for example, connections in Mental Networks usually change due to learning, while connections in Social Networks change due to various social dynamics. For adaptive networks, separate procedural specifications are often added for the adaptation process. Accordingly, modelers have to deal with a less transparent, hybrid specification, part of which is often more at a programming level than at a modeling level. This book presents an overall Network-Oriented Modeling approach that makes designing adaptive network models much easier, because the adaptation process, too, is modeled in a neat, declarative, and conceptually transparent Network-Oriented Modeling manner, like the network itself. Thanks to this approach, no procedural, algorithmic, or programming skills are needed to design complex adaptive network models. A dedicated software environment is available to run these adaptive network models from their high-level specifications. Moreover, because adaptive networks are described in a network format as well, the approach can simply be applied iteratively, so that higher-order adaptive networks in which network adaptation itself is adaptive (second-order adaptation), too can be modeled just as easily. For example, this can be applied to model metaplasticity in cognitive neuroscience, or second-order adaptation in biological and social contexts. The book illustrates the usefulness of this approach via numerous examples of complex (higher-order) adaptive network models for a wide variety of biological, mental, and social processes. The book is suitable for multidisciplinary Master’s and Ph.D. students without assuming much prior knowledge, although also some elementary mathematical analysis is involved. Given the detailed information provided, it can be used as an introduction to Network-Oriented Modeling for adaptive networks. The material is ideally suited for teaching undergraduate and graduate students with multidisciplinary backgrounds or interests. Lecturers will find additional material such as slides, assignments, and software.

Author : George A. Rovithakis
Publisher : Springer Science & Business Media
ISBN 13 : 1447107853
Total Pages : 203 pages
Book Rating : 4.59/5 ( download)

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Download or read book Adaptive Control with Recurrent High-order Neural Networks written by George A. Rovithakis and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 203 pages. Available in PDF, EPUB and Kindle. Book excerpt: The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new applications, new philosophies ... , new challenges. Much of this development work resides in industrial reports, feasibility study papers and the reports of advanced collaborative projects. The series offers an opportunity for researchers to present an extended exposition of such new work in all aspects of industrial control for wider and rapid dissemination. Neural networks is one of those areas where an initial burst of enthusiasm and optimism leads to an explosion of papers in the journals and many presentations at conferences but it is only in the last decade that significant theoretical work on stability, convergence and robustness for the use of neural networks in control systems has been tackled. George Rovithakis and Manolis Christodoulou have been interested in these theoretical problems and in the practical aspects of neural network applications to industrial problems. This very welcome addition to the Advances in Industrial Control series provides a succinct report of their research. The neural network model at the core of their work is the Recurrent High Order Neural Network (RHONN) and a complete theoretical and simulation development is presented. Different readers will find different aspects of the development of interest. The last chapter of the monograph discusses the problem of manufacturing or production process scheduling.

Author : Federico Battiston
Publisher : Springer Nature
ISBN 13 : 3030913740
Total Pages : 436 pages
Book Rating : 4.48/5 ( download)

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Download or read book Higher-Order Systems written by Federico Battiston and published by Springer Nature. This book was released on 2022-04-26 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book discusses the potential of higher-order interactions to model real-world relational systems. Over the last decade, networks have emerged as the paradigmatic framework to model complex systems. Yet, as simple collections of nodes and links, they are intrinsically limited to pairwise interactions, limiting our ability to describe, understand, and predict complex phenomena which arise from higher-order interactions. Here we introduce the new modeling framework of higher-order systems, where hypergraphs and simplicial complexes are used to describe complex patterns of interactions among any number of agents. This book is intended both as a first introduction and an overview of the state of the art of this rapidly emerging field, serving as a reference for network scientists interested in better modeling the interconnected world we live in.

Author : Rosa Maria Benito
Publisher : Springer Nature
ISBN 13 : 3030934098
Total Pages : 896 pages
Book Rating : 4.95/5 ( download)

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Download or read book Complex Networks & Their Applications X written by Rosa Maria Benito and published by Springer Nature. This book was released on 2022-01-01 with total page 896 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students, and practitioners a unique update on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the X International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2021). The carefully selected papers cover a wide range of theoretical topics such as network models and measures; community structure, network dynamics; diffusion, epidemics and spreading processes; resilience and control as well as all the main network applications, including social and political networks; networks in finance and economics; biological and neuroscience networks, and technological networks.

Author : Hocine Cherifi
Publisher : Springer Nature
ISBN 13 : 3031211278
Total Pages : 667 pages
Book Rating : 4.70/5 ( download)

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Download or read book Complex Networks and Their Applications XI written by Hocine Cherifi and published by Springer Nature. This book was released on 2023-01-03 with total page 667 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students, and practitioners a unique update on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the XI International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2022). The carefully selected papers cover a wide range of theoretical topics such as network models and measures; community structure, network dynamics; diffusion, epidemics, and spreading processes; resilience and control as well as all the main network applications, including social and political networks; networks in finance and economics; biological and neuroscience networks and technological networks.

Author : Bao-Liang Lu
Publisher : Springer Science & Business Media
ISBN 13 : 3642132774
Total Pages : 787 pages
Book Rating : 4.73/5 ( download)

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Download or read book Advances in Neural Networks -- ISNN 2010 written by Bao-Liang Lu and published by Springer Science & Business Media. This book was released on 2010-05-21 with total page 787 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book and its sister volume constitutes the proceedings of the 7th International Symposium on Neural Networks, ISNN 2010, held in Shanghai, China, June 6-9, 2010. The 170 revised full papers of Part I and Part II were carefully selected from 591 submissions and focus on topics such as Neurophysiological Foundation, Theory and Models, Learning and Inference, and Neurodynamics. The second volume, Part II (LNCS 6064) covers the following 5 topics: SVM and Kernel Methods, Vision and Image, Data Mining and Text Analysis, BCI and Brain Imaging, and applications.

Author : Cornelia Denz
Publisher : Springer Science & Business Media
ISBN 13 : 3663122727
Total Pages : 467 pages
Book Rating : 4.22/5 ( download)

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Download or read book Optical Neural Networks written by Cornelia Denz and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 467 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the next years neural networks and systems amenable to instructions will extend their influence in science and technology. A prominent point of interest in this field is assigned to optical networks: they are small and flexible, and due to their ability of parallel processing they are devoted to the construction of small systems. This monograph explains the fundamentals of optical neural networks to physicists, engineers and device constructors.