Download or read book Associative Neural Memories written by Mohamad H. Hassoun and published by . This book was released on 1993 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Brings together significant works on associative neural memory theory (architecture, learning, analysis, and design) and hardware implementation (VLSI and opto-electronic) by leading international researchers. The volume is organized into an introductory chapter and four parts: biological and psychological connections, artificial associative neural memory models, analysis of memory dynamics and capacity, and implementation. Annotation copyright by Book News, Inc., Portland, OR
Download or read book Artificial Neural Networks ICANN 2008 written by Vera Kurkova-Pohlova and published by Springer. This book was released on 2008-08-29 with total page 1012 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two volume set LNCS 5163 and LNCS 5164 constitutes the refereed proceedings of the 18th International Conference on Artificial Neural Networks, ICANN 2008, held in Prague Czech Republic, in September 2008. The 200 revised full papers presented were carefully reviewed and selected from more than 300 submissions. The second volume is devoted to pattern recognition and data analysis, hardware and embedded systems, computational neuroscience, connectionistic cognitive science, neuroinformatics and neural dynamics. it also contains papers from two special sessions coupling, synchronies, and firing patterns: from cognition to disease, and constructive neural networks and two workshops new trends in self-organization and optimization of artificial neural networks, and adaptive mechanisms of the perception-action cycle.
Download or read book Self Organization and Associative Memory written by Teuvo Kohonen and published by Springer. This book was released on 2012-12-06 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: Two significant things have happened since the writing of the first edition in 1983. One of them is recent arousal of strong interest in general aspects of "neural computing", or "neural networks", as the previous neural models are nowadays called. The incentive, of course, has been to develop new com puters. Especially it may have been felt that the so-called fifth-generation computers, based on conventional logic programming, do not yet contain in formation processing principles of the same type as those encountered in the brain. All new ideas for the "neural computers" are, of course, welcome. On the other hand, it is not very easy to see what kind of restrictions there exist to their implementation. In order to approach this problem systematically, cer tain lines of thought, disciplines, and criteria should be followed. It is the pur pose of the added Chapter 9 to reflect upon such problems from a general point of view. Another important thing is a boom of new hardware technologies for dis tributed associative memories, especially high-density semiconductor circuits, and optical materials and components. The era is very close when the parallel processors can be made all-optical. Several working associative memory archi tectures, based solely on optical technologies, have been constructed in recent years. For this reason it was felt necessary to include a separate chapter (Chap. 10) which deals with the optical associative memories. Part of its con tents is taken over from the first edition.
Download or read book Progress in Pattern Recognition Image Analysis and Applications written by José Ruiz-Shulcloper and published by Springer. This book was released on 2008-09-17 with total page 828 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 13th Iberoamerican Congress on Pattern Recognition, CIARP 2008, held in Havana, Cuba, in September 2008. The 93 revised full papers presented together with 3 keynote articles were carefully reviewed and selected from 182 submissions. The papers are organized in topical sections on signal analysis for characterization and filtering, analysis of shape and texture, analysis of speech and language, data mining, clustering of images and documents, statistical pattern recognition, classification and description of objects, classification and edition, geometric image analysis, neural networks, computer vision, image coding, associative memories and neural networks, interpolation and video tracking, images analysis, music and speech analysis, as well as classifier combination and document filtering.
Download or read book Parallel Models of Associative Memory written by Geoffrey E. Hinton and published by Psychology Press. This book was released on 2014-02-25 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: This update of the 1981 classic on neural networks includes new commentaries by the authors that show how the original ideas are related to subsequent developments. As researchers continue to uncover ways of applying the complex information processing abilities of neural networks, they give these models an exciting future which may well involve revolutionary developments in understanding the brain and the mind -- developments that may allow researchers to build adaptive intelligent machines. The original chapters show where the ideas came from and the new commentaries show where they are going.
Download or read book Associative Memory Cells Basic Units of Memory Trace written by Jin-Hui Wang and published by Springer Nature. This book was released on 2019-09-10 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on associative memory cells and their working principles, which can be applied to associative memories and memory-relevant cognitions. Providing comprehensive diagrams, it presents the author's personal perspectives on pathology and therapeutic strategies for memory deficits in patients suffering from neurological diseases and psychiatric disorders. Associative learning is a common approach to acquire multiple associated signals, including knowledge, experiences and skills from natural environments or social interaction. The identification of the cellular and molecular mechanisms underlying associative memory is important in furthering our understanding of the principles of memory formation and memory-relevant behaviors as well as in developing therapeutic strategies that enhance memory capacity in healthy individuals and improve memory deficit in patients suffering from neurological disease and psychiatric disorders. Although a series of hypotheses about neural substrates for associative memory has been proposed, numerous questions still need to be addressed, especially the basic units and their working principle in engrams and circuits specific for various memory patterns. This book summarizes the developments concerning associative memory cells reported in current and past literature, providing a valuable overview of the field for neuroscientists, psychologists and students.
Download or read book Parallel Models of Associative Memory written by Geoffrey E. Hinton and published by Psychology Press. This book was released on 2014-02-25 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: This update of the 1981 classic on neural networks includes new commentaries by the authors that show how the original ideas are related to subsequent developments. As researchers continue to uncover ways of applying the complex information processing abilities of neural networks, they give these models an exciting future which may well involve revolutionary developments in understanding the brain and the mind -- developments that may allow researchers to build adaptive intelligent machines. The original chapters show where the ideas came from and the new commentaries show where they are going.
Download or read book Associative Memory written by T. Kohonen and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: About the Scope of This Text This book contains two types of material ~ first, the many divergent and often diffuse meanings given to the concepts of association, associative memory, and associative recaZZ are expounded. A review of this kind was felt necessary because there apparently does not exist any single monograph which could serve as a reference to these topics. But the presentation of the main body of this text is motivated by quite other reasons: in recent years, plenty of interesting mathematical and system-theoretical material has been published which makes it possible to gain a view of associative memory which is different from the conventional abstract and computationally oriented approaches. It seems that the basic operation of associative memory, the storage of information together with the relations or links between the data items, and the selective recall of stored information relative to a piece of key or cue information presented, is not restricted to certain computer-technological implementations but can also be reflected in more general mathematically describable processes in certain physical or other systems, especially in their adaptive state changes. It further seems that some generally known forms of associative memory, namely, certain computer technological artifacts, or abstract systems of concepts or data, are in fact special representations of a class of processes characterized as associative memory.
Download or read book Constructing Associative Memories Using Neural Networks written by Xin Xu and published by . This book was released on 1988* with total page 23 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Consciousness Transitions written by Hans Liljenström and published by Elsevier. This book was released on 2011-10-13 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: It was not long ago when the consciousness was not considered a problem for science. However, this has now changed and the problem of consciousness is considered the greatest challenge to science. In the last decade, a great number of books and articles have been published in the field, but very few have focused on the how consciousness evolves and develops, and what characterizes the transitions between different conscious states, in animals and humans. This book addresses these questions. Renowned researchers from different fields of science (including neurobiology, evolutionary biology, ethology, cognitive science, computational neuroscience and philosophy) contribute with their results and theories in this book, making it a unique collection of the state-of-the-art of this young field of consciousness studies. First book on the topic Focus on different levels of consciousness, including: Evolutionary, developmental, and functional Highly interdisciplinary
Download or read book Artificial Neural Nets and Genetic Algorithms written by Andrej Dobnikar and published by Springer Science & Business Media. This book was released on 1999-07-15 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: From the contents: Neural networks – theory and applications: NNs (= neural networks) classifier on continuous data domains– quantum associative memory – a new class of neuron-like discrete filters to image processing – modular NNs for improving generalisation properties – presynaptic inhibition modelling for image processing application – NN recognition system for a curvature primal sketch – NN based nonlinear temporal-spatial noise rejection system – relaxation rate for improving Hopfield network – Oja's NN and influence of the learning gain on its dynamics Genetic algorithms – theory and applications: transposition: a biological-inspired mechanism to use with GAs (= genetic algorithms) – GA for decision tree induction – optimising decision classifications using GAs – scheduling tasks with intertask communication onto multiprocessors by GAs – design of robust networks with GA – effect of degenerate coding on GAs – multiple traffic signal control using a GA – evolving musical harmonisation – niched-penalty approach for constraint handling in GAs – GA with dynamic population size – GA with dynamic niche clustering for multimodal function optimisation Soft computing and uncertainty: self-adaptation of evolutionary constructed decision trees by information spreading – evolutionary programming of near optimal NNs
Download or read book Neural Plasticity and Memory written by Federico Bermudez-Rattoni and published by CRC Press. This book was released on 2007-04-17 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive, multidisciplinary review, Neural Plasticity and Memory: From Genes to Brain Imaging provides an in-depth, up-to-date analysis of the study of the neurobiology of memory. Leading specialists share their scientific experience in the field, covering a wide range of topics where molecular, genetic, behavioral, and brain imaging techniq
Download or read book Synthesis of Neural Networks for Associative Memories written by Zanjun Lu and published by . This book was released on 1999 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Neural Networks and Statistical Learning written by Ke-Lin Du and published by Springer Science & Business Media. This book was released on 2013-12-09 with total page 834 pages. Available in PDF, EPUB and Kindle. Book excerpt: Providing a broad but in-depth introduction to neural network and machine learning in a statistical framework, this book provides a single, comprehensive resource for study and further research. All the major popular neural network models and statistical learning approaches are covered with examples and exercises in every chapter to develop a practical working understanding of the content. Each of the twenty-five chapters includes state-of-the-art descriptions and important research results on the respective topics. The broad coverage includes the multilayer perceptron, the Hopfield network, associative memory models, clustering models and algorithms, the radial basis function network, recurrent neural networks, principal component analysis, nonnegative matrix factorization, independent component analysis, discriminant analysis, support vector machines, kernel methods, reinforcement learning, probabilistic and Bayesian networks, data fusion and ensemble learning, fuzzy sets and logic, neurofuzzy models, hardware implementations, and some machine learning topics. Applications to biometric/bioinformatics and data mining are also included. Focusing on the prominent accomplishments and their practical aspects, academic and technical staff, graduate students and researchers will find that this provides a solid foundation and encompassing reference for the fields of neural networks, pattern recognition, signal processing, machine learning, computational intelligence, and data mining.
Download or read book Models of Neural Networks III written by Eytan Domany and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book An Introduction to Neural Networks written by Kevin Gurney and published by CRC Press. This book was released on 2018-10-08 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: Though mathematical ideas underpin the study of neural networks, the author presents the fundamentals without the full mathematical apparatus. All aspects of the field are tackled, including artificial neurons as models of their real counterparts; the geometry of network action in pattern space; gradient descent methods, including back-propagation; associative memory and Hopfield nets; and self-organization and feature maps. The traditionally difficult topic of adaptive resonance theory is clarified within a hierarchical description of its operation. The book also includes several real-world examples to provide a concrete focus. This should enhance its appeal to those involved in the design, construction and management of networks in commercial environments and who wish to improve their understanding of network simulator packages. As a comprehensive and highly accessible introduction to one of the most important topics in cognitive and computer science, this volume should interest a wide range of readers, both students and professionals, in cognitive science, psychology, computer science and electrical engineering.
Download or read book Neural Networks written by Berndt Müller and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural Networks presents concepts of neural-network models and techniques of parallel distributed processing in a three-step approach: - A brief overview of the neural structure of the brain and the history of neural-network modeling introduces to associative memory, preceptrons, feature-sensitive networks, learning strategies, and practical applications. - The second part covers subjects like statistical physics of spin glasses, the mean-field theory of the Hopfield model, and the "space of interactions" approach to the storage capacity of neural networks. - The final part discusses nine programs with practical demonstrations of neural-network models. The software and source code in C are on a 3 1/2" MS-DOS diskette can be run with Microsoft, Borland, Turbo-C, or compatible compilers.