Advanced topics on cellular self-organizing nets and chaotic nonlinear dynamics to model and control complex systems /
This book focuses on the research topics investigated during the three-year research project funded by the Italian Ministero dell'Istruzione, dell'Universite e della Ricerca (MIUR: Ministry of Education, University and Research) under the FIRB project RBNE01CW3M. With the aim of introduci...
| Други автори: | Caponetto, R. 1966-, Fortuna, L. 1953-, Frasca, Mattia. |
|---|---|
| Формат: | Електронна книга |
| Език: | English |
| Публикувано: |
Singapore :
World Scientific,
℗♭2008.
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| Серия: |
World Scientific series on nonlinear science. Monographs and treatises ;
v. 63. |
| Предмети: | |
| Онлайн достъп: |
http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=521160 |
Съдържание:
- 1. The CNN paradigm for complexity. 1.1. Introduction. 1.2. The 3D-CNN model. 1.3. E[symbol]: an universal emulator for complex systems. 1.4. Emergence of forms in 3D-CNNs. 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 tip-sample force model. 3.5. Conclusions
- 4. Control and parameter estimation of systems with low-dimensional chaos
- the role of peak-to-peak dynamics. 4.1. Introduction. 4.2. Peak-to-peak 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 long-range 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.