Hierarchy And Dynamics In Neural Networks
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| Author | : Rolf Kötter |
| Publisher | : Frontiers E-books |
| Total Pages | : 97 |
| Release | : 2012-01-01 |
| Genre | : |
| ISBN | : 2889190102 |
Hierarchy is a central feature in the organisation of complex biological systems and particularly the structure and function of neural networks. While other aspects of brain connectivity such as regionalisation, modularity or motif composition have been discussed elsewhere, no detailed analysis has been presented so far on the role of hierarchy and its connection to brain dynamics. Recent discussions among many of our colleagues have shown an increasing interest in hierarchy (of spatial, temporal and dynamic features), and this is an emerging key question in neuroscience as well as generally in the field of network science, due to its links with concepts of control, efficiency and development across scales (e.g. Hilgetag et al. Science, 1996; Ravasz et al. Science, 2002; Bassett et al. PNAS, 2006; Mueller-Linow et al. PLoS Comp. Biol., in press). The proposed Research Topic will address recent findings from a theoretical as well as experimental perspective including contributions under the following four headings: 1) Topology: Detecting and characterizing network hierarchy; 2) Experiments: Neural dynamics across hierarchical scales; 3) Dynamics: Activity spread, oscillations, and synchronization in hierarchical networks; 4) Dynamics: Stable functioning and information processing in hierarchical networks.
| Author | : Gerold Baier |
| Publisher | : World Scientific |
| Total Pages | : 403 |
| Release | : 1991-03-29 |
| Genre | : |
| ISBN | : 981461890X |
This collection of articles introduces the idea of a hierarchical order in chaotic systems and natural phenomena. To understand nature, nonlinear sciences use a multidisciplinary perspective. Therefore the book integrates research work of different fields: experimental evidence for the theory drawn from physics, biology and chemistry; theoretical progress in mathematical treatment, numerical techniques and graphical methods of nonlinear sciences; and to not-yet-understood philosophical and fundamental problems related to chaos and cosmos, chaos and quantum mechanics or evolutionary dynamics. Featuring the most recent advances in nonlinear dynamics this collection should provide an indispensable reference source and starting point for further research concerning dynamical and hierarchical chaotic systems. Besides this book is in honor of Professor O E Rössler, one of the pioneers of Chaos Theory, who celebrated his 50th birthday in May 1990.
| Author | : Sven Behnke |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 230 |
| Release | : 2003-08-21 |
| Genre | : Computers |
| ISBN | : 3540407227 |
Human performance in visual perception by far exceeds the performance of contemporary computer vision systems. While humans are able to perceive their environment almost instantly and reliably under a wide range of conditions, computer vision systems work well only under controlled conditions in limited domains. This book sets out to reproduce the robustness and speed of human perception by proposing a hierarchical neural network architecture for iterative image interpretation. The proposed architecture can be trained using unsupervised and supervised learning techniques. Applications of the proposed architecture are illustrated using small networks. Furthermore, several larger networks were trained to perform various nontrivial computer vision tasks.
| Author | : Institute of Medicine |
| Publisher | : National Academies Press |
| Total Pages | : 180 |
| Release | : 1991-02-01 |
| Genre | : Computers |
| ISBN | : 0309044979 |
Significant advances in brain research have been made, but investigators who face the resulting explosion of data need new methods to integrate the pieces of the "brain puzzle." Based on the expertise of more than 100 neuroscientists and computer specialists, this new volume examines how computer technology can meet that need. Featuring outstanding color photography, the book presents an overview of the complexity of brain research, which covers the spectrum from human behavior to genetic mechanisms. Advances in vision, substance abuse, pain, and schizophrenia are highlighted. The committee explores the potential benefits of computer graphics, database systems, and communications networks in neuroscience and reviews the available technology. Recommendations center on a proposed Brain Mapping Initiative, with an agenda for implementation and a look at issues such as privacy and accessibility.
| Author | : Harald Ruda |
| Publisher | : |
| Total Pages | : 6 |
| Release | : 1996 |
| Genre | : Decision making |
| ISBN | : |
| Author | : Leonid I. Perlovsky |
| Publisher | : Springer |
| Total Pages | : 369 |
| Release | : 2007-08-26 |
| Genre | : Technology & Engineering |
| ISBN | : 3540732675 |
Experimental evidence in humans and other mammalians indicates that complex neurodynamics is crucial for the emergence of higher-level intelligence. Dynamical neural systems with encoding in limit cycle and non-convergent attractors have gained increasing popularity in the past decade. The role of synchronization, desynchronization, and intermittent synchronization on cognition has been studied extensively by various authors, in particular by authors contributing to the present volume. This book addresses dynamical aspects of brain functions and cognition.
| Author | : Sven Behnke |
| Publisher | : Springer |
| Total Pages | : 230 |
| Release | : 2003-11-18 |
| Genre | : Computers |
| ISBN | : 3540451692 |
Human performance in visual perception by far exceeds the performance of contemporary computer vision systems. While humans are able to perceive their environment almost instantly and reliably under a wide range of conditions, computer vision systems work well only under controlled conditions in limited domains. This book sets out to reproduce the robustness and speed of human perception by proposing a hierarchical neural network architecture for iterative image interpretation. The proposed architecture can be trained using unsupervised and supervised learning techniques. Applications of the proposed architecture are illustrated using small networks. Furthermore, several larger networks were trained to perform various nontrivial computer vision tasks.
| Author | : Fouad Sabry |
| Publisher | : One Billion Knowledgeable |
| Total Pages | : 120 |
| Release | : 2023-06-20 |
| Genre | : Computers |
| ISBN | : |
What Is Hybrid Neural Networks The phrase "hybrid neural network" can refer to either biological neural networks that interact with artificial neuronal models or artificial neural networks that also have a symbolic component. Both of these interpretations are possible. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Hybrid neural network Chapter 2: Connectionism Chapter 3: Computational neuroscience Chapter 4: Symbolic artificial intelligence Chapter 5: Neuromorphic engineering Chapter 6: Recurrent neural network Chapter 7: Neural network Chapter 8: Neuro-fuzzy Chapter 9: Spiking neural network Chapter 10: Hierarchical temporal memory (II) Answering the public top questions about hybrid neural networks. (III) Real world examples for the usage of hybrid neural networks in many fields. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of hybrid neural networks. What Is Artificial Intelligence Series The artificial intelligence book series provides comprehensive coverage in over 200 topics. Each ebook covers a specific Artificial Intelligence topic in depth, written by experts in the field. The series aims to give readers a thorough understanding of the concepts, techniques, history and applications of artificial intelligence. Topics covered include machine learning, deep learning, neural networks, computer vision, natural language processing, robotics, ethics and more. The ebooks are written for professionals, students, and anyone interested in learning about the latest developments in this rapidly advancing field. The artificial intelligence book series provides an in-depth yet accessible exploration, from the fundamental concepts to the state-of-the-art research. With over 200 volumes, readers gain a thorough grounding in all aspects of Artificial Intelligence. The ebooks are designed to build knowledge systematically, with later volumes building on the foundations laid by earlier ones. This comprehensive series is an indispensable resource for anyone seeking to develop expertise in artificial intelligence.
| Author | : Alwyn Scott |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 362 |
| Release | : 2007-12-14 |
| Genre | : Science |
| ISBN | : 0387224637 |
This book will be of interest to anyone who wishes to know what role mathematics can play in attempting to comprehend the dynamics of the human brain. It also aims to serve as a general introduction to neuromathematics. The book gives the reader a qualitative understanding and working knowledge of useful mathematical applications to the field of neuroscience. The book is readable by those who have little knowledge of mathematics for neuroscience but are committed to begin acquiring such knowledge.
| Author | : Dietmar Plenz |
| Publisher | : John Wiley & Sons |
| Total Pages | : 734 |
| Release | : 2014-04-14 |
| Genre | : Computers |
| ISBN | : 3527651020 |
Neurowissenschaftler suchen nach Antworten auf die Fragen, wie wir lernen und Information speichern, welche Prozesse im Gehirn verantwortlich sind und in welchem Zeitrahmen diese ablaufen. Die Konzepte, die aus der Physik kommen und weiterentwickelt werden, können in Medizin und Soziologie, aber auch in Robotik und Bildanalyse Anwendung finden. Zentrales Thema dieses Buches sind die sogenannten kritischen Phänomene im Gehirn. Diese werden mithilfe mathematischer und physikalischer Modelle beschrieben, mit denen man auch Erdbeben, Waldbrände oder die Ausbreitung von Epidemien modellieren kann. Neuere Erkenntnisse haben ergeben, dass diese selbstgeordneten Instabilitäten auch im Nervensystem auftreten. Dieses Referenzwerk stellt theoretische und experimentelle Befunde internationaler Gehirnforschung vor zeichnet die Perspektiven dieses neuen Forschungsfeldes auf.
