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Weakly Connected Neural Networks

Weakly Connected Neural Networks
Author: Frank C. Hoppensteadt
Publisher: Springer Science & Business Media
Total Pages: 404
Release: 2012-12-06
Genre: Mathematics
ISBN: 1461218284

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Devoted to local and global analysis of weakly connected systems with applications to neurosciences, this book uses bifurcation theory and canonical models as the major tools of analysis. It presents a systematic and well motivated development of both weakly connected system theory and mathematical neuroscience, addressing bifurcations in neuron and brain dynamics, synaptic organisations of the brain, and the nature of neural codes. The authors present classical results together with the most recent developments in the field, making this a useful reference for researchers and graduate students in various branches of mathematical neuroscience.


Ground-State Coding in Partially Connected Neural Networks

Ground-State Coding in Partially Connected Neural Networks
Author: National Aeronautics and Space Adm Nasa
Publisher: Independently Published
Total Pages: 38
Release: 2018-12-31
Genre:
ISBN: 9781792747328

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Patterns over (-1,0,1) define, by their outer products, partially connected neural networks, consisting of internally strongly connected, externally weakly connected subnetworks. The connectivity patterns may have highly organized structures, such as lattices and fractal trees or nests. Subpatterns over (-1,1) define the subcodes stored in the subnetwork, that agree in their common bits. It is first shown that the code words are locally stable stares of the network, provided that each of the subcodes consists of mutually orthogonal words or of, at most, two words. Then it is shown that if each of the subcodes consists of two orthogonal words, the code words are the unique ground states (absolute minima) of the Hamiltonian associated with the network. The regions of attraction associated with the code words are shown to grow with the number of subnetworks sharing each of the neurons. Depending on the particular network architecture, the code sizes of partially connected networks can be vastly greater than those of fully connected ones and their error correction capabilities can be significantly greater than those of the disconnected subnetworks. The codes associated with lattice-structured and hierarchical networks are discussed in some detail. Baram, Yoram Ames Research Center NASA-TM-102239, A-89256, NAS 1.15:102239 RTOP 505-67-21...


Advances in Information Processing and Protection

Advances in Information Processing and Protection
Author: Jerzy Pejas
Publisher: Springer Science & Business Media
Total Pages: 455
Release: 2007-09-29
Genre: Computers
ISBN: 0387731377

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This book contains a selection of the best papers given at an international conference on advanced computer systems. The Advanced Computer Systems Conference was held in October 2006, in Miedzyzdroje, Poland. The book is organized into four topical areas: Artificial Intelligence; Computer Security and Safety; Image Analysis, Graphics and Biometrics; and Computer Simulation and Data Analysis.


The Handbook of Brain Theory and Neural Networks

The Handbook of Brain Theory and Neural Networks
Author: Michael A. Arbib
Publisher: MIT Press
Total Pages: 1328
Release: 2003
Genre: Neural circuitry
ISBN: 0262011972

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This second edition presents the enormous progress made in recent years in the many subfields related to the two great questions : how does the brain work? and, How can we build intelligent machines? This second edition greatly increases the coverage of models of fundamental neurobiology, cognitive neuroscience, and neural network approaches to language. (Midwest).


Natural Biodynamics

Natural Biodynamics
Author: Vladimir G Ivancevic
Publisher: World Scientific
Total Pages: 1036
Release: 2005-11-29
Genre: Mathematics
ISBN: 981447911X

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This comprehensive volume is a graduate-level text in human biodynamics, written in the unified categorical language of modern differential geometry and topology. Combining mathematics, physics and robotics with human physiology, this is the first book that describes all levels of human biodynamics, from musculo-skeletal mechanics to the higher brain functions. The book develops and uses a variety of research methods, ranging from chaos theory and Haken's synergetics, through quantum mechanics, to nonlinear control and artificial intelligence, to provide the means to understand, predict and control the behavior of human-like systems in their full neuro-musculo-skeletal complexity. The applications of this unique scientific methodology range from prediction of human neuro-musculo-skeletal injuries to brain-like control of humanoid robots.


Bifurcations in Brain Dynamics

Bifurcations in Brain Dynamics
Author: Eugene M. Izhikevich
Publisher:
Total Pages: 402
Release: 1996
Genre: Brain
ISBN:

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Handbook of Dynamical Systems

Handbook of Dynamical Systems
Author: B. Fiedler
Publisher: Gulf Professional Publishing
Total Pages: 1099
Release: 2002-02-21
Genre: Science
ISBN: 0080532845

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This handbook is volume II in a series collecting mathematical state-of-the-art surveys in the field of dynamical systems. Much of this field has developed from interactions with other areas of science, and this volume shows how concepts of dynamical systems further the understanding of mathematical issues that arise in applications. Although modeling issues are addressed, the central theme is the mathematically rigorous investigation of the resulting differential equations and their dynamic behavior. However, the authors and editors have made an effort to ensure readability on a non-technical level for mathematicians from other fields and for other scientists and engineers. The eighteen surveys collected here do not aspire to encyclopedic completeness, but present selected paradigms. The surveys are grouped into those emphasizing finite-dimensional methods, numerics, topological methods, and partial differential equations. Application areas include the dynamics of neural networks, fluid flows, nonlinear optics, and many others. While the survey articles can be read independently, they deeply share recurrent themes from dynamical systems. Attractors, bifurcations, center manifolds, dimension reduction, ergodicity, homoclinicity, hyperbolicity, invariant and inertial manifolds, normal forms, recurrence, shift dynamics, stability, to namejust a few, are ubiquitous dynamical concepts throughout the articles.


Graph Algorithms for Data Science

Graph Algorithms for Data Science
Author: Tomaž Bratanic
Publisher: Simon and Schuster
Total Pages: 350
Release: 2024-02-27
Genre: Computers
ISBN: 1617299464

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Graph Algorithms for Data Science teaches you how to construct graphs from both structured and unstructured data. You'll learn how the flexible Cypher query language can be used to easily manipulate graph structures, and extract amazing insights. Graph Algorithms for Data Science is a hands-on guide to working with graph-based data in applications. It's filled with fascinating and fun projects, demonstrating the ins-and-outs of graphs. You'll gain practical skills by analyzing Twitter, building graphs with NLP techniques, and much more. These powerful graph algorithms are explained in clear, jargon-free text and illustrations that makes them easy to apply to your own projects.