Organization Of Neural Networks
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Organization Of Neural Networks
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Author : Werner von Seelen
language : en
Publisher:
Release Date : 1988
Organization Of Neural Networks written by Werner von Seelen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988 with Brain categories.
Neural Networks In Organizational Research
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Author : David Scarborough
language : en
Publisher: American Psychological Association (APA)
Release Date : 2006
Neural Networks In Organizational Research written by David Scarborough and has been published by American Psychological Association (APA) this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Business & Economics categories.
"Behavioral scientists working in organizations today have access to unprecedented amounts of data. Networked computing and software tools are changing the landscape of organizational research in fundamental ways. Information technology facilitates creation of vast amounts of data. In organizational research, online surveys, interactive interviews, computer-based assessment, and other digital tools have become a preferred medium for collecting self-report and opinion data. Other unobtrusive, nontraditional sources of behavioral observation data are coming into use. Measures of online behavior and databases maintained by corporations and government agencies for other purposes can be a useful source of research data. Concurrent with expanding data availability, analytic capability and processing capacity have improved dramatically.
Neuromorphic Computing Principles And Organization
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Author : Abderazek Ben Abdallah
language : en
Publisher: Springer Nature
Release Date : 2022-05-31
Neuromorphic Computing Principles And Organization written by Abderazek Ben Abdallah and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Computers categories.
This book focuses on neuromorphic computing principles and organization and how to build fault-tolerant scalable hardware for large and medium scale spiking neural networks with learning capabilities. In addition, the book describes in a comprehensive way the organization and how to design a spike-based neuromorphic system to perform network of spiking neurons communication, computing, and adaptive learning for emerging AI applications. The book begins with an overview of neuromorphic computing systems and explores the fundamental concepts of artificial neural networks. Next, we discuss artificial neurons and how they have evolved in their representation of biological neuronal dynamics. Afterward, we discuss implementing these neural networks in neuron models, storage technologies, inter-neuron communication networks, learning, and various design approaches. Then, comes the fundamental design principle to build an efficient neuromorphic system in hardware. The challenges that need to be solved toward building a spiking neural network architecture with many synapses are discussed. Learning in neuromorphic computing systems and the major emerging memory technologies that promise neuromorphic computing are then given. A particular chapter of this book is dedicated to the circuits and architectures used for communication in neuromorphic systems. In particular, the Network-on-Chip fabric is introduced for receiving and transmitting spikes following the Address Event Representation (AER) protocol and the memory accessing method. In addition, the interconnect design principle is covered to help understand the overall concept of on-chip and off-chip communication. Advanced on-chip interconnect technologies, including si-photonic three-dimensional interconnects and fault-tolerant routing algorithms, are also given. The book also covers the main threats of reliability and discusses several recovery methods for multicore neuromorphic systems. This is important for reliable processing in several embedded neuromorphic applications. A reconfigurable design approach that supports multiple target applications via dynamic reconfigurability, network topology independence, and network expandability is also described in the subsequent chapters. The book ends with a case study about a real hardware-software design of a reliable three-dimensional digital neuromorphic processor geared explicitly toward the 3D-ICs biological brain’s three-dimensional structure. The platform enables high integration density and slight spike delay of spiking networks and features a scalable design. We present methods for fault detection and recovery in a neuromorphic system as well. Neuromorphic Computing Principles and Organization is an excellent resource for researchers, scientists, graduate students, and hardware-software engineers dealing with the ever-increasing demands on fault-tolerance, scalability, and low power consumption. It is also an excellent resource for teaching advanced undergraduate and graduate students about the fundamentals concepts, organization, and actual hardware-software design of reliable neuromorphic systems with learning and fault-tolerance capabilities.
Self Organization In Neural Networks
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Author : Daniel Merson Kammen
language : en
Publisher:
Release Date : 1988
Self Organization In Neural Networks written by Daniel Merson Kammen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988 with Information theory in biology categories.
Development And Organization Of Neural Networks
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Author : Leon N. Cooper
language : en
Publisher:
Release Date : 1988
Development And Organization Of Neural Networks written by Leon N. Cooper and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988 with Cells categories.
Previously, the author had proposed a single cell theory for the development of selectivity and ocular dominance in a neural network. During the contract period, this theory has been generalized to incorporate more realistic neural networks that approximate the actual anatomy of small regions of cortex. In particular, he has analyzed a network consisting of excitatory and inhibitory cells, both which may receive information from LGN. These two cortical cell types then interact through intracortical connections that are either excitatory or inhibitory. This investigation of the evolution of a cell in this mean field network of fixed points that have been obtained previously in the single cell theory are successfully generalized here. In addition, the author has been able to make explicit further statements concerning the independent effects of excitatory and inhibitory neurons on selectivity and ocular dominance. For example, shutting off inhibitory cells lessens selectivity and alters ocular dominance (masked synapses). These inhibitory cells may be selective, but there is no theoretical necessity that they be so.
Neural Organization
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Author : Michael A. Arbib
language : en
Publisher: MIT Press
Release Date : 1998
Neural Organization written by Michael A. Arbib and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Medical categories.
In Neural Organization, Arbib, Erdi, and Szentagothai integrate structural, functional, and dynamical approaches to the interaction of brain models and neurobiologcal experiments. Both structure-based "bottom-up" and function- based "top-down" models offer coherent concepts by which to evaluate the experimental data. The goal of this book is to point out the advantages of a multidisciplinary, multistrategied approach to the brain.Part I of Neural Organization provides a detailed introduction to each of the three areas of structure, function, and dynamics. Structure refers to the anatomical aspects of the brain and the relations between different brain regions. Function refers to skills and behaviors, which are explained by means of functional schemas and biologically based neural networks. Dynamics refers to the use of a mathematical framework to analyze the temporal change of neural activities and synaptic connectivities that underlie brain development and plasticity--in terms of both detailed single-cell models and large-scale network models.In part II, the authors show how their systematic approach can be used to analyze specific parts of the nervous system--the olfactory system, hippocampus, thalamus, cerebral cortex, cerebellum, and basal ganglia--as well as to integrate data from the study of brain regions, functional models, and the dynamics of neural networks. In conclusion, they offer a plan for the use of their methods in the development of cognitive neuroscience."
Self Organization In Neural Networks As Model For The Development Of Motorcontrol
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Author : Jacob Johannes van Heijst
language : en
Publisher:
Release Date : 1998
Self Organization In Neural Networks As Model For The Development Of Motorcontrol written by Jacob Johannes van Heijst and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with categories.
Models Of Neural Networks Iii
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Author : Eytan Domany
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Models Of Neural Networks Iii written by Eytan Domany and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Science categories.
One of the most challenging and fascinating problems of the theory of neural nets is that of asymptotic behavior, of how a system behaves as time proceeds. This is of particular relevance to many practical applications. Here we focus on association, generalization, and representation. We turn to the last topic first. The introductory chapter, "Global Analysis of Recurrent Neural Net works," by Andreas Herz presents an in-depth analysis of how to construct a Lyapunov function for various types of dynamics and neural coding. It includes a review of the recent work with John Hopfield on integrate-and fire neurons with local interactions. The chapter, "Receptive Fields and Maps in the Visual Cortex: Models of Ocular Dominance and Orientation Columns" by Ken Miller, explains how the primary visual cortex may asymptotically gain its specific structure through a self-organization process based on Hebbian learning. His argu ment since has been shown to be rather susceptible to generalization.
Neural Networks In Organizational Research
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Author : David Scarborough
language : en
Publisher:
Release Date : 2006
Neural Networks In Organizational Research written by David Scarborough and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with categories.
"Behavioral scientists working in organizations today have access to unprecedented amounts of data. Networked computing and software tools are changing the landscape of organizational research in fundamental ways. Information technology facilitates creation of vast amounts of data. In organizational research, online surveys, interactive interviews, computer-based assessment, and other digital tools have become a preferred medium for collecting self-report and opinion data. Other unobtrusive, nontraditional sources of behavioral observation data are coming into use. Measures of online behavior and databases maintained by corporations and government agencies for other purposes can be a useful source of research data. Concurrent with expanding data availability, analytic capability and processing capacity have improved dramatically.
Dynamics And Self Organization Of Locally Coupled Neural Networks
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Author : Patrick Thiran
language : en
Publisher: EPFL Press
Release Date : 1997-01-01
Dynamics And Self Organization Of Locally Coupled Neural Networks written by Patrick Thiran and has been published by EPFL Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997-01-01 with Neural networks (Computer science) categories.