Hierarchy and dynamics in neural networks PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Hierarchy and dynamics in neural networks PDF full book. Access full book title Hierarchy and dynamics in neural networks by Rolf Kötter. Download full books in PDF and EPUB format.
Author: Rolf Kötter Publisher: Frontiers E-books ISBN: 2889190102 Category : Languages : en Pages : 97
Book Description
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: Rolf Kötter Publisher: Frontiers E-books ISBN: 2889190102 Category : Languages : en Pages : 97
Book Description
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 ISBN: 981461890X Category : Languages : en Pages : 403
Book Description
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 ISBN: 3540407227 Category : Computers Languages : en Pages : 230
Book Description
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 ISBN: 0309044979 Category : Computers Languages : en Pages : 180
Book Description
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: J.G. Taylor Publisher: Springer ISBN: Category : Computers Languages : en Pages : 388
Book Description
Neural Network Dynamics is the latest volume in the Perspectives in Neural Computing series. It contains papers presented at the 1991 Workshop on Complex Dynamics in Neural Networks, held at IIASS in Vietri, Italy. The workshop encompassed a wide range of topics in which neural networks play a fundamental role, and aimed to bridge the gap between neural computation and computational neuroscience. The papers - which have been updated where necessary to include new results - are divided into four sections, covering the foundations of neural network dynamics, oscillatory neural networks, as well as scientific and biological applications of neural networks. Among the topics discussed are: A general analysis of neural network activity; Descriptions of various network architectures and nodes; Correlated neuronal firing; A theoretical framework for analyzing the behaviour of real and simulated neuronal networks; The structural properties of proteins; Nuclear phenomenology; Resonance searches in high energy physics; The investigation of information storage; Visual cortical architecture; Visual processing. Neural Network Dynamics is the first volume to cover neural networks and computational neuroscience in such detail. Although it is primarily aimed at researchers and postgraduate students in the above disciplines, it will also be of interest to researchers in electrical engineering, medicine, psychology and philosophy.
Author: Sven Behnke Publisher: Springer ISBN: 3540451692 Category : Computers Languages : en Pages : 230
Book Description
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: Paul W. Glimcher Publisher: Academic Press ISBN: 0123914698 Category : Psychology Languages : en Pages : 606
Book Description
In the years since it first published, Neuroeconomics: Decision Making and the Brain has become the standard reference and textbook in the burgeoning field of neuroeconomics. The second edition, a nearly complete revision of this landmark book, will set a new standard. This new edition features five sections designed to serve as both classroom-friendly introductions to each of the major subareas in neuroeconomics, and as advanced synopses of all that has been accomplished in the last two decades in this rapidly expanding academic discipline. The first of these sections provides useful introductions to the disciplines of microeconomics, the psychology of judgment and decision, computational neuroscience, and anthropology for scholars and students seeking interdisciplinary breadth. The second section provides an overview of how human and animal preferences are represented in the mammalian nervous systems. Chapters on risk, time preferences, social preferences, emotion, pharmacology, and common neural currencies—each written by leading experts—lay out the foundations of neuroeconomic thought. The third section contains both overview and in-depth chapters on the fundamentals of reinforcement learning, value learning, and value representation. The fourth section, “The Neural Mechanisms for Choice, integrates what is known about the decision-making architecture into state-of-the-art models of how we make choices. The final section embeds these mechanisms in a larger social context, showing how these mechanisms function during social decision-making in both humans and animals. The book provides a historically rich exposition in each of its chapters and emphasizes both the accomplishments and the controversies in the field. A clear explanatory style and a single expository voice characterize all chapters, making core issues in economics, psychology, and neuroscience accessible to scholars from all disciplines. The volume is essential reading for anyone interested in neuroeconomics in particular or decision making in general. Editors and contributing authors are among the acknowledged experts and founders in the field, making this the authoritative reference for neuroeconomics Suitable as an advanced undergraduate or graduate textbook as well as a thorough reference for active researchers Introductory chapters on economics, psychology, neuroscience, and anthropology provide students and scholars from any discipline with the keys to understanding this interdisciplinary field Detailed chapters on subjects that include reinforcement learning, risk, inter-temporal choice, drift-diffusion models, game theory, and prospect theory make this an invaluable reference Published in association with the Society for Neuroeconomics—www.neuroeconomics.org Full-color presentation throughout with numerous carefully selected illustrations to highlight key concepts
Author: Fouad Sabry Publisher: One Billion Knowledgeable ISBN: Category : Computers Languages : en Pages : 120
Book Description
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 ISBN: 0387224637 Category : Science Languages : en Pages : 362
Book Description
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: Rolf Kötter
Author: Rolf Kötter
Author: Gerold Baier
Author: Sven Behnke
Author: Institute of Medicine
Author: J.G. Taylor
Author: Harald Ruda
Author: Sven Behnke
Author: Paul W. Glimcher
Author: Fouad Sabry
Author: Alwyn Scott