Description 
1 online resource (xvi, 191 pages) : illustrations (some color) 
Series 
World Scientific series on nonlinear science. Series A, Monographs and treatises ; v. 63 

World Scientific series on nonlinear science. Series A, Monographs and treatises ; v. 63.

Contents 
1. The CNN paradigm for complexity. 1.1. Introduction. 1.2. The 3DCNN model. 1.3. E[symbol]: an universal emulator for complex systems. 1.4. Emergence of forms in 3DCNNs. 1.5. Conclusions  2. Emergent phenomena in neuroscience. 2.1. Introductory material: neurons and models. 2.2. Electronic implementation of neuron models. 2.3. Local activity theory for systems of IO neurons. 2.4. Simulation of IO systems: emerging results. 2.5. Networks of HR neurons. 2.6. Neurons in presence of noise. 2.7. Conclusions  3. Frequency analysis and identification in atomic force microscopy. 3.1. Introduction. 3.2. AFM modeling. 3.3. Frequency analysis via harmonic balance. 3.4. Identification of the tipsample force model. 3.5. Conclusions  4. Control and parameter estimation of systems with lowdimensional chaos  the role of peaktopeak dynamics. 4.1. Introduction. 4.2. Peaktopeak dynamics. 4.3. Control system design. 4.4. Parameter estimation. 4.5. Concluding remarks  5. Synchronization of complex networks. 5.1. Introduction. 5.2. Synchronization of interacting oscillators. 5.3. From local to longrange connections. 5.4. The master stability function. 5.5. Key elements for the assessing of synchronizability. 5.6. Synchronizability of weighted networks. 5.7. Synchronization of coupled oscillators: some significant results. 5.8. Conclusions  6. Economic sector identification in a set of stocks traded at the New York Exchange: a comparative analysis. 6.1. Introduction. 6.2. The data set. 6.3. Random matrix theory. 6.4. Hierarchical clustering methods. 6.5. The planar maximally filtered graph. 6.6. Conclusions  7. Innovation systems by nonlinear networks. 7.1. Introduction. 7.2. Cellular automata model. 7.3. Innovation models based on CNNs. 7.4. Simulation results. 7.5. Conclusions 
Summary 
This book focuses on the research topics investigated during the threeyear research project funded by the Italian Ministero dell'Istruzione, dell'Universitè e della Ricerca (MIUR: Ministry of Education, University and Research) under the FIRB project RBNE01CW3M. With the aim of introducing newer perspectives of the research on complexity, the final results of the project are presented after a general introduction to the subject. The book is intended to provide researchers, PhD students, and people involved in research projects in companies with the basic fundamentals of complex systems and the advanced project results recently obtained 
Bibliography 
Includes bibliographical references and index 
Notes 
Print version record 
Subject 
Computational complexity.


Nonlinear systems  Mathematical models


Selforganizing maps.


System theory  Mathematical models


MATHEMATICS  Set Theory.


Computational complexity


Nonlinear systems  Mathematical models


Selforganizing maps


System theory  Mathematical models

Form 
Electronic book

Author 
Caponetto, R. (Riccardo), 1966


Fortuna, L. (Luigi), 1953


Frasca, Mattia

LC no. 
2008301004 
ISBN 
9812814051 

9789812814050 

9812814043 

9789812814043 
