A View Of Kanerva S Sparse Distributed Memory
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A View Of Kanerva S Sparse Distributed Memory
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Author :
language : en
Publisher:
Release Date : 1986
A View Of Kanerva S Sparse Distributed Memory written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1986 with categories.
Comparison Between Sparsely Distributed Memory And Hopfield Type Neural Network Models
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Author :
language : en
Publisher:
Release Date : 1986
Comparison Between Sparsely Distributed Memory And Hopfield Type Neural Network Models written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1986 with categories.
Notes On Implementation Of Sparsely Distributed Memory
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Author :
language : en
Publisher:
Release Date : 1986
Notes On Implementation Of Sparsely Distributed Memory written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1986 with categories.
Electronic Engineering And Computing Technology
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Author : Len Gelman
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-04-21
Electronic Engineering And Computing Technology written by Len Gelman 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 2010-04-21 with Technology & Engineering categories.
Electronic Engineering and Computing Technology contains sixty-one revised and extended research articles written by prominent researchers participating in the conference. Topics covered include Control Engineering, Network Management, Wireless Networks, Biotechnology, Signal Processing, Computational Intelligence, Computational Statistics, Internet Computing, High Performance Computing, and industrial applications. Electronic Engineering and Computing Technology will offer the state of art of tremendous advances in electronic engineering and computing technology and also serve as an excellent reference work for researchers and graduate students working with/on electronic engineering and computing technology.
Sparse Distributed Memory And Related Models
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Author : Pentti Kanerva
language : en
Publisher:
Release Date : 1992
Sparse Distributed Memory And Related Models written by Pentti Kanerva and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with Distributed artificial intelligence categories.
Abstract: "This paper describes sparse distributed memory (SDM) as a neural-net associative memory. It is characterized by two weight matrices and by a large internal dimension -- the number of hidden units is much larger than the number of input or output units. The first matrix, A, is fixed and possibly random, and the second matrix, C, is modifiable. The paper compares and contrasts SDM to (1) computer memory, (2) correlation-matrix memory, (3) feed-forward artificial neural network, (4) cortex of the cerebellum, (5) Marr and Albus models of the cerebellum, and (6) Albus' cerebellar model arithmetic computer (CMAC). Several variations of the basic SDM design are discussed: the selected-coordinate and hyperplane designs of Jaeckel, the pseudorandom associative neural memory of Hassoun, and SDM with real-valued input variables by Prager and Fallside. SDM research conducted mainly at RIACS in 1986-1991 is highlighted."
Physical Neuromorphic Computing And Its Industrial Applications
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Author : Toshiyuki Yamane
language : en
Publisher: Frontiers Media SA
Release Date : 2023-08-02
Physical Neuromorphic Computing And Its Industrial Applications written by Toshiyuki Yamane and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-02 with Science categories.
Computer Vision Eccv 2022
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Author : Shai Avidan
language : en
Publisher: Springer Nature
Release Date : 2022-10-20
Computer Vision Eccv 2022 written by Shai Avidan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-20 with Computers categories.
The 39-volume set, comprising the LNCS books 13661 until 13699, constitutes the refereed proceedings of the 17th European Conference on Computer Vision, ECCV 2022, held in Tel Aviv, Israel, during October 23–27, 2022. The 1645 papers presented in these proceedings were carefully reviewed and selected from a total of 5804 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation.
Principles Of Neural Coding
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Author : Rodrigo Quian Quiroga
language : en
Publisher: CRC Press
Release Date : 2013-05-06
Principles Of Neural Coding written by Rodrigo Quian Quiroga and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-06 with Medical categories.
Understanding how populations of neurons encode information is the challenge faced by researchers in the field of neural coding. Focusing on the many mysteries and marvels of the mind has prompted a prominent team of experts in the field to put their heads together and fire up a book on the subject. Simply titled Principles of Neural Coding, this book covers the complexities of this discipline. It centers on some of the major developments in this area and presents a complete assessment of how neurons in the brain encode information. The book collaborators contribute various chapters that describe results in different systems (visual, auditory, somatosensory perception, etc.) and different species (monkeys, rats, humans, etc). Concentrating on the recording and analysis of the firing of single and multiple neurons, and the analysis and recording of other integrative measures of network activity and network states—such as local field potentials or current source densities—is the basis of the introductory chapters. Provides a comprehensive and interdisciplinary approach Describes topics of interest to a wide range of researchers The book then moves forward with the description of the principles of neural coding for different functions and in different species and concludes with theoretical and modeling works describing how information processing functions are implemented. The text not only contains the most important experimental findings, but gives an overview of the main methodological aspects for studying neural coding. In addition, the book describes alternative approaches based on simulations with neural networks and in silico modeling in this highly interdisciplinary topic. It can serve as an important reference to students and professionals.
Brain Theory From A Circuits And Systems Perspective
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Author : John Robert Burger
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-05-31
Brain Theory From A Circuits And Systems Perspective written by John Robert Burger 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 2013-05-31 with Medical categories.
This book models an idealized neuron as being driven by basic electrical elements, the goal being to systematically characterize the logical properties of neural pulses. In order to constitute a system, neurons as pulsating devices may be represented using novel circuit elements as delineated in this book. A plausible brain system is implied by the delineated elements and logically follows from known and likely properties of a neuron. New to electrical science are novel pulse-related circuit elements involving recursive neurons. A recursive neuron, when properly excited, produces a self-sustaining pulse train that when sampled, provides a true output with a specified probability, and a false output with complementary probability. Because of its similarity to the qubits of quantum mechanics, the recursive pulsating neuron is termed a simulated qubit. Recursive neurons easily function as controlled toggle devices and so are capable of massively parallel calculations, this being a new dimension in brain functioning as described in this book. Simulated qubits and their possibilities are compared to the qubits of quantum physics. Included in the book are suggested neural circuits for associative memory search via a randomized process of cue selection, and neural circuits for priority calculations. These serve to select returns from long term memory, which in turn determines one's next conscious thought or action based on past memorized experiences. The book reports on proposals involving electron tunneling between synapses, and quantum computations within neurons. Although not a textbook, there are easy exercises at the ends of chapters, and in the appendix there are twelve simulation experiments concerning neurons.
An Introduction To Neural Networks
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Author : James A. Anderson
language : en
Publisher: MIT Press
Release Date : 1995
An Introduction To Neural Networks written by James A. Anderson and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Computers categories.
An Introduction to Neural Networks falls into a new ecological niche for texts. Based on notes that have been class-tested for more than a decade, it is aimed at cognitive science and neuroscience students who need to understand brain function in terms of computational modeling, and at engineers who want to go beyond formal algorithms to applications and computing strategies. It is the only current text to approach networks from a broad neuroscience and cognitive science perspective, with an emphasis on the biology and psychology behind the assumptions of the models, as well as on what the models might be used for. It describes the mathematical and computational tools needed and provides an account of the author's own ideas. Students learn how to teach arithmetic to a neural network and get a short course on linear associative memory and adaptive maps. They are introduced to the author's brain-state-in-a-box (BSB) model and are provided with some of the neurobiological background necessary for a firm grasp of the general subject. The field now known as neural networks has split in recent years into two major groups, mirrored in the texts that are currently available: the engineers who are primarily interested in practical applications of the new adaptive, parallel computing technology, and the cognitive scientists and neuroscientists who are interested in scientific applications. As the gap between these two groups widens, Anderson notes that the academics have tended to drift off into irrelevant, often excessively abstract research while the engineers have lost contact with the source of ideas in the field. Neuroscience, he points out, provides a rich and valuable source of ideas about data representation and setting up the data representation is the major part of neural network programming. Both cognitive science and neuroscience give insights into how this can be done effectively: cognitive science suggests what to compute and neuroscience suggests how to compute it.