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Author | Title | Accn# | Year | Item Type | Claims |
| 11 |
Lehnert, Judith |
Controlling Synchronization Patterns in Complex Networks |
I09860 |
2016 |
eBook |
|
| 12 |
Helias, Moritz |
Statistical Field Theory for Neural Networks |
I09583 |
2020 |
eBook |
|
| 13 |
Hutt, Axel |
Synergetics |
I09580 |
2020 |
eBook |
|
| 14 |
Czischek, Stefanie |
Neural-Network Simulation of Strongly Correlated Quantum Systems |
I09120 |
2020 |
eBook |
|
| 15 |
Lubashevsky, Ihor |
Physics of the Human Mind |
I08732 |
2017 |
eBook |
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11.
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| Title | Controlling Synchronization Patterns in Complex Networks |
| Author(s) | Lehnert, Judith |
| Publication | Cham, Springer International Publishing, 2016. |
| Description | XV, 203 p : online resource |
| Abstract Note | This research aims to achieve a fundamental understanding of synchronization and its interplay with the topology of complex networks. Synchronization is a ubiquitous phenomenon observed in different contexts in physics, chemistry, biology, medicine and engineering. Most prominently, synchronization takes place in the brain, where it is associated with several cognitive capacities but is - in abundance - a characteristic of neurological diseases. Besides zero-lag synchrony, group and cluster states are considered, enabling a description and study of complex synchronization patterns within the presented theory. Adaptive control methods are developed, which allow the control of synchronization in scenarios where parameters drift or are unknown. These methods are, therefore, of particular interest for experimental setups or technological applications. The theoretical framework is demonstrated on generic models, coupled chemical oscillators and several detailed examples of neural networks |
| ISBN,Price | 9783319251158 |
| Keyword(s) | 1. Applications of Graph Theory and Complex Networks
2. DYNAMICAL SYSTEMS
3. DYNAMICS
4. EBOOK
5. EBOOK - SPRINGER
6. Mathematical Models of Cognitive Processes and Neural Networks
7. Neural networks (Computer science)??
8. PHYSICAL CHEMISTRY
9. PHYSICS
10. SYSTEM THEORY
11. Systems Theory, Control
12. VIBRATION
13. Vibration, Dynamical Systems, Control
|
| Item Type | eBook |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I09860 |
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On Shelf |
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12.
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| Title | Statistical Field Theory for Neural Networks |
| Author(s) | Helias, Moritz;Dahmen, David |
| Publication | Cham, Springer International Publishing, 2020. |
| Description | XVII, 203 p. 127 illus., 5 illus. in color : online resource |
| Abstract Note | This book presents a self-contained introduction to techniques from field theory applied to stochastic and collective dynamics in neuronal networks. These powerful analytical techniques, which are well established in other fields of physics, are the basis of current developments and offer solutions to pressing open problems in theoretical neuroscience and also machine learning. They enable a systematic and quantitative understanding of the dynamics in recurrent and stochastic neuronal networks. This book is intended for physicists, mathematicians, and computer scientists and it is designed for self-study by researchers who want to enter the field or as the main text for a one semester course at advanced undergraduate or graduate level. The theoretical concepts presented in this book are systematically developed from the very beginning, which only requires basic knowledge of analysis and linear algebra |
| ISBN,Price | 9783030464448 |
| Keyword(s) | 1. EBOOK
2. EBOOK - SPRINGER
3. MACHINE LEARNING
4. Mathematical Models of Cognitive Processes and Neural Networks
5. MATHEMATICAL STATISTICS
6. Neural networks (Computer science)??
7. Neurosciences
8. Probability and Statistics in Computer Science
9. STATISTICAL PHYSICS
10. Statistical Physics and Dynamical Systems
|
| Item Type | eBook |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I09583 |
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On Shelf |
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13.
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| Title | Synergetics |
| Author(s) | Hutt, Axel;Haken, Hermann |
| Publication | New York, NY, Springer US, 2020. |
| Description | 223 illus., 95 illus. in color. eReference : online resource |
| Abstract Note | This volume of the ???Encyclopedia of Complexity and Systems Science, Second Edition??? (ECSS), introduces the fundamental physical and mathematical concepts underlying the theory of complex physical, chemical, and biological systems. Numerous applications illustrate how these concepts explain observed phenomena in our daily lives, which range from spatio-temporal patterns in fluids from atmospheric turbulence in hurricanes and tornadoes to feedback dynamics of laser intensity to structures in cities and rhythms in the brain. The spontaneous formation of well-organized structures out of microscopic system components and their interactions is one of the most fascinating and challenging phenomena for scientists to understand. Biological systems may also exhibit organized structures emanating from interactions of cells and their networks. For instance, underlying structures in the brain emerge as certain mental states, the ability to coordinate movement, or pathologies such as tremor or epileptic seizures. When we try to explain or understand these extremely complex biological phenomena, it is natural to ask whether analogous processes of self-organization may be found in much simpler systems of the inanimate world. In recent decades, it has become increasingly evident that there exist numerous examples in physical and chemical systems in which well-organized spatio-temporal structures arise out of disordered states. As in living organisms, the functioning of these systems can be maintained only by a flux of energy (and matter) through them. Synergetics combines elements from physics and mathematics to explain how a diversity of systems obey the same basic principles. All chapters in this volume have been thoroughly revised and updated from the first edition of ECSS. The second edition also includes new or expanded coverage of such topics as chaotic dynamics in laser systems and neurons, novel insights into the relation of classical chaos and quantum dynamics, and how noise in the brain tunes observed neural activity and controls animal and human behavior. |
| ISBN,Price | 9781071604212 |
| Keyword(s) | 1. Applications of Nonlinear Dynamics and Chaos Theory
2. COMPLEX SYSTEMS
3. COMPLEXITY
4. COMPUTATIONAL COMPLEXITY
5. EBOOK
6. EBOOK - SPRINGER
7. Mathematical Models of Cognitive Processes and Neural Networks
8. Neural networks (Computer science)??
9. STATISTICAL PHYSICS
10. Statistical Physics and Dynamical Systems
11. SYSTEM THEORY
12. Systems biology
|
| Item Type | eBook |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I09580 |
|
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On Shelf |
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14.
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| Title | Neural-Network Simulation of Strongly Correlated Quantum Systems |
| Author(s) | Czischek, Stefanie |
| Publication | Cham, Springer International Publishing, 2020. |
| Description | XV, 205 p. 51 illus., 48 illus. in color : online resource |
| Abstract Note | Quantum systems with many degrees of freedom are inherently difficult to describe and simulate quantitatively. The space of possible states is, in general, exponentially large in the number of degrees of freedom such as the number of particles it contains. Standard digital high-performance computing is generally too weak to capture all the necessary details, such that alternative quantum simulation devices have been proposed as a solution. Artificial neural networks, with their high non-local connectivity between the neuron degrees of freedom, may soon gain importance in simulating static and dynamical behavior of quantum systems. Particularly promising candidates are neuromorphic realizations based on analog electronic circuits which are being developed to capture, e.g., the functioning of biologically relevant networks. In turn, such neuromorphic systems may be used to measure and control real quantum many-body systems online. This thesis lays an important foundation for the realization of quantum simulations by means of neuromorphic hardware, for using quantum physics as an input to classical neural nets and, in turn, for using network results to be fed back to quantum systems. The necessary foundations on both sides, quantum physics and artificial neural networks, are described, providing a valuable reference for researchers from these different communities who need to understand the foundations of both |
| ISBN,Price | 9783030527150 |
| Keyword(s) | 1. CONDENSED MATTER
2. CONDENSED MATTER PHYSICS
3. EBOOK
4. EBOOK - SPRINGER
5. MACHINE LEARNING
6. Mathematical Models of Cognitive Processes and Neural Networks
7. Neural networks (Computer science)??
8. QUANTUM PHYSICS
|
| Item Type | eBook |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I09120 |
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On Shelf |
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15.
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| Title | Physics of the Human Mind |
| Author(s) | Lubashevsky, Ihor |
| Publication | Cham, Springer International Publishing, 2017. |
| Description | XIV, 380 p. 83 illus., 41 illus. in color : online resource |
| Abstract Note | This book tackles the challenging question which mathematical formalisms and possibly new physical notions should be developed for quantitatively describing human cognition and behavior, in addition to the ones already developed in the physical and cognitive sciences. Indeed, physics is widely used in modeling social systems, where, in particular, new branches of science such as sociophysics and econophysics have arisen. However, many if not most characteristic features of humans like willingness, emotions, memory, future prediction, and moral norms, to name but a few, are not yet properly reflected in the paradigms of physical thought and theory. The choice of a relevant formalism for modeling mental phenomena requires the comprehension of the general philosophical questions related to the mind-body problem. Plausible answers to these questions are investigated and reviewed, notions and concepts to be used or to be taken into account are developed and some challenging questions are posed as open problems. This text addresses theoretical physicists and neuroscientists modeling any systems and processes where human factors play a crucial role, philosophers interested in applying philosophical concepts to the construction of mathematical models, and the mathematically oriented psychologists and sociologists, whose research is fundamentally related to modeling mental processes |
| ISBN,Price | 9783319517063 |
| Keyword(s) | 1. Cognitive psychology
2. Data-driven Science, Modeling and Theory Building
3. EBOOK
4. EBOOK - SPRINGER
5. ECONOPHYSICS
6. Mathematical Methods in Physics
7. Mathematical Models of Cognitive Processes and Neural Networks
8. Neural networks (Computer science)??
9. PHILOSOPHY OF MIND
10. PHYSICS
11. Sociophysics
|
| Item Type | eBook |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I08732 |
|
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On Shelf |
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