The study of networks has experienced a tremendous increase of interest over the past decade. From the viewpoint of physics, much of this interest arises from the fact that networks grasp the main essence of complex systems, namely the long-range interactions between individual elements. This book demonstrates that, within the methodology of statistical physics, networks can be understood on three different descriptory levels. Firstly, it is shown that random matrix theory can be used to describe random features of networks. This also makes the acquiring of non-random properties possible, which is exemplified based on high-frequency financial data. Secondly, aiming towards the understanding of real-world networks (which deviate strongly from the random case) an understanding based on equilibrium statistical mechanics is proposed. It is shown that a Hamiltonian motivated from utility theory allows to describe real-world evidence accurately. Finally, a specific model of network formation is developed to describe out-of-equilibrium aspects of cooperation and network formation. The three descriptory levels are discussed under a unifying viewpoint.

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Christoly Biely is a physicist from the Complex Systems Research Group (Vienna), who also works in the financial industry. Dr. Biely''s research interests comprise statistical physics, network theory and finance. He has published his work in well-renowned journals such as Physical Review, Physica D and Quantitative Finance.

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**Book Description **Condition: New. Publisher/Verlag: VDM Verlag Dr. Müller | Applications in Econophysics | The study of networks has experienced a tremendous increase of interest over the past decade. From the viewpoint of physics, much of this interest arises from the fact that networks grasp the main essence of complex systems, namely the long-range interactions between individual elements. This book demonstrates that, within the methodology of statistical physics, networks can be understood on three different descriptory levels. Firstly, it is shown that random matrix theory can be used to describe random features of networks. This also makes the acquiring of non-random properties possible, which is exemplified based on high-frequency financial data. Secondly, aiming towards the understanding of real-world networks (which deviate strongly from the random case) an understanding based on equilibrium statistical mechanics is proposed. It is shown that a Hamiltonian motivated from utility theory allows to describe real-world evidence accurately. Finally,a specific model of network formation is developed to describe out-of-equilibrium aspects of cooperation and network formation. The three descriptory levels are discussed under a unifying viewpoint. | Format: Paperback | Language/Sprache: english | 185 gr | 132 pp. Seller Inventory # K9783639031782

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**Book Description **VDM Verlag Dr. Mueller e.K., Germany, 2013. Paperback. Condition: New. Language: English . Brand New Book ***** Print on Demand *****.The study of networks has experienced a tremendous increase of interest over the past decade. From the viewpoint of physics, much of this interest arises from the fact that networks grasp the main essence of complex systems, namely the long-range interactions between individual elements. This book demonstrates that, within the methodology of statistical physics, networks can be understood on three different descriptory levels. Firstly, it is shown that random matrix theory can be used to describe random features of networks. This also makes the acquiring of non-random properties possible, which is exemplified based on high-frequency financial data. Secondly, aiming towards the understanding of real-world networks (which deviate strongly from the random case) an understanding based on equilibrium statistical mechanics is proposed. It is shown that a Hamiltonian motivated from utility theory allows to describe real-world evidence accurately. Finally, a specific model of network formation is developed to describe out-of-equilibrium aspects of cooperation and network formation. The three descriptory levels are discussed under a unifying viewpoint. Seller Inventory # AAV9783639031782

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**Book Description **VDM Verlag Dr. Müller E.K. Okt 2013, 2013. Taschenbuch. Condition: Neu. Neuware - The study of networks has experienced a tremendous increase of interest over the past decade. From the viewpoint of physics, much of this interest arises from the fact that networks grasp the main essence of complex systems, namely the long-range interactions between individual elements. This book demonstrates that, within the methodology of statistical physics, networks can be understood on three different descriptory levels. Firstly, it is shown that random matrix theory can be used to describe random features of networks. This also makes the acquiring of non-random properties possible, which is exemplified based on high-frequency financial data. Secondly, aiming towards the understanding of real-world networks (which deviate strongly from the random case) an understanding based on equilibrium statistical mechanics is proposed. It is shown that a Hamiltonian motivated from utility theory allows to describe real-world evidence accurately. Finally,a specific model of network formation is developed to describe out-of-equilibrium aspects of cooperation and network formation. The three descriptory levels are discussed under a unifying viewpoint. 132 pp. Englisch. Seller Inventory # 9783639031782

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**Book Description **VDM Verlag Dr. Müller E.K. Okt 2013, 2013. Taschenbuch. Condition: Neu. Neuware - The study of networks has experienced a tremendous increase of interest over the past decade. From the viewpoint of physics, much of this interest arises from the fact that networks grasp the main essence of complex systems, namely the long-range interactions between individual elements. This book demonstrates that, within the methodology of statistical physics, networks can be understood on three different descriptory levels. Firstly, it is shown that random matrix theory can be used to describe random features of networks. This also makes the acquiring of non-random properties possible, which is exemplified based on high-frequency financial data. Secondly, aiming towards the understanding of real-world networks (which deviate strongly from the random case) an understanding based on equilibrium statistical mechanics is proposed. It is shown that a Hamiltonian motivated from utility theory allows to describe real-world evidence accurately. Finally,a specific model of network formation is developed to describe out-of-equilibrium aspects of cooperation and network formation. The three descriptory levels are discussed under a unifying viewpoint. 132 pp. Englisch. Seller Inventory # 9783639031782

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**Book Description **VDM Verlag. Paperback. Condition: New. 132 pages. Dimensions: 8.8in. x 6.0in. x 0.3in.The study of networks has experienced a tremendous increase of interest over the past decade. From the viewpoint of physics, much of this interest arises from the fact that networks grasp the main essence of complex systems, namely the long-range interactions between individual elements. This book demonstrates that, within the methodology of statistical physics, networks can be understood on three different descriptory levels. Firstly, it is shown that random matrix theory can be used to describe random features of networks. This also makes the acquiring of non-random properties possible, which is exemplified based on high-frequency financial data. Secondly, aiming towards the understanding of real-world networks (which deviate strongly from the random case) an understanding based on equilibrium statistical mechanics is proposed. It is shown that a Hamiltonian motivated from utility theory allows to describe real-world evidence accurately. Finally, a specific model of network formation is developed to describe out-of-equilibrium aspects of cooperation and network formation. The three descriptory levels are discussed under a unifying viewpoint. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN. Paperback. Seller Inventory # 9783639031782

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**Book Description **VDM Verlag Dr. Mueller e.K., 2008. Paperback. Condition: New. Seller Inventory # DADAX3639031784