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Sensory Neural Networks
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Book Synopsis Dynamics of Sensory and Cognitive Processing by the Brain by : Theodore Melnechuk
Download or read book Dynamics of Sensory and Cognitive Processing by the Brain written by Theodore Melnechuk and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: In neurophysiology, the emphasis has been on single-unit studies for a quarter century, since the sensory work by Lettwin and coworkers and by Hubel and Wiesel, the cen tral work by Mountcastle, the motor work by the late Evarts, and so on. In recent years, however, field potentials - and a more global approach general ly - have been receiving renewed and increasing attention. This is a result of new findings made possible by technical and conceptual advances and by the confirma tion and augmentation of earlier findings that were widely ignored for being contro versial or inexplicable. To survey the state of this active field, a conference was held in West Berlin in August 1985 that attempted to cover all of the new approaches to the study of brain function. The approaches and emphases were very varied: basic and applied, electric and magnetic, EEG and EP/ERP, connectionistic and field, global and local fields, surface and multielectrode, low frequencies and high frequencies, linear and non linear. The conference comprised sessions of invited lectures, a panel session of seven speakers on "How brains may work," and a concluding survey of relevant methodologies. The conference showed that the combination of concepts, methods, and results could open up new important vistas in brain research. Included here are the proceedings of the conference, updated and revised by the authors. Several attendees who did not present papers at the conference later ac cepted my invitation to write chapters for the book.
Book Synopsis Introduction to Dynamic Modeling of Neuro-Sensory Systems by : Robert B. Northrop
Download or read book Introduction to Dynamic Modeling of Neuro-Sensory Systems written by Robert B. Northrop and published by CRC Press. This book was released on 2000-11-27 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although neural modeling has a long history, most of the texts available on the subject are quite limited in scope, dealing primarily with the simulation of large-scale biological neural networks applicable to describing brain function. Introduction to Dynamic Modeling of Neuro-Sensory Systems presents the mathematical tools and methods that can de
Book Synopsis Sensory Neural Networks by : Bahram Nabet
Download or read book Sensory Neural Networks written by Bahram Nabet and published by . This book was released on 2018 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Sensory information is detected and transformed by sensory neural networks before reaching higher levels of processing. These networks need to perform significant processing tasks while being compatible with the following levels. Lateral inhibition is a mechanism of local neuronal interaction that produces significant global properties. This book discusses those sensory neural networks influenced by nonlinear lateral inhibition. It features biological bases of lateral inhibition models, computational properties of these models that stress their short term adaptive behavior, their relation to recent activity in neural networks and connectionist systems, their use for image processing applications, and their application to motion detection. Descriptions from different technologies of analog hardware implementations of these classes of networks are described and results from implementations that corroborate theoretical analysis and show technologically desirable applications are presented. The book also uses nonlinear mathematical techniques to analyze temporal and spatial behavior of models presented within the text. Sensory Neural Networks: Lateral Inhibition is an interdisciplinary work that will prove useful to neural network theorists, biologists, circuit designers, and vision scientists."--Provided by publisher.
Book Synopsis An Introduction to Neural Networks by : James A. Anderson
Download or read book An Introduction to Neural Networks written by James A. Anderson and published by MIT Press. This book was released on 1995 with total page 680 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Multivariate Analysis of Data in Sensory Science by : T. Naes
Download or read book Multivariate Analysis of Data in Sensory Science written by T. Naes and published by Elsevier. This book was released on 1996-02-01 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: The state-of-the-art of multivariate analysis in sensory science is described in this volume. Both methods for aggregated and individual sensory profiles are discussed. Processes and results are presented in such a way that they can be understood not only by statisticians but also by experienced sensory panel leaders and users of sensory analysis.The techniques presented are focused on examples and interpretation rather than on the technical aspects, with an emphasis on new and important methods which are possibly not so well known to scientists in the field. Important features of the book are discussions on the relationship among the methods with a strong accent on the connection between problems and methods. All procedures presented are described in relation to sensory data and not as completely general statistical techniques.Sensory scientists, applied statisticians, chemometricians, those working in consumer science, food scientists and agronomers will find this book of value.
Book Synopsis Motivation, Emotion, and Goal Direction in Neural Networks by : Daniel S. Levine
Download or read book Motivation, Emotion, and Goal Direction in Neural Networks written by Daniel S. Levine and published by Psychology Press. This book was released on 2014-01-14 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: The articles gathered in this volume represent examples of a unique approach to the study of mental phenomena: a blend of theory and experiment, informed not just by easily measurable laboratory data but also by human introspection. Subjects such as approach and avoidance, desire and fear, and novelty and habit are studied as natural events that may not exactly correspond to, but at least correlate with, some (known or unknown) electrical and chemical events in the brain.
Book Synopsis Advances in Neural Networks – ISNN 2018 by : Tingwen Huang
Download or read book Advances in Neural Networks – ISNN 2018 written by Tingwen Huang and published by Springer. This book was released on 2018-05-25 with total page 879 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 15th International Symposium on Neural Networks, ISNN 2018, held in Minsk, Belarus in June 2018.The 98 revised regular papers presented in this volume were carefully reviewed and selected from 214 submissions. The papers cover many topics of neural network-related research including intelligent control, neurodynamic analysis, bio-signal, bioinformatics and biomedical engineering, clustering, classification, forecasting, models, algorithms, cognitive computation, machine learning, and optimization.
Book Synopsis Artificial Neural Nets. Problem Solving Methods by : José Mira
Download or read book Artificial Neural Nets. Problem Solving Methods written by José Mira and published by Springer Science & Business Media. This book was released on 2003-05-22 with total page 845 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNCS 2686 and LNCS 2687 constitute the refereed proceedings of the 7th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2003, held in Maó, Menorca, Spain in June 2003. The 197 revised papers presented were carefully reviewed and selected for inclusion in the book and address the following topics: mathematical and computational methods in neural modelling, neurophysiological data analysis and modelling, structural and functional models of neurons, learning and other plasticity phenomena, complex systems dynamics, cognitive processes and artificial intelligence, methodologies for net design, bio-inspired systems and engineering, and applications in a broad variety of fields.
Book Synopsis Neural Networks and Animal Behavior by : Magnus Enquist
Download or read book Neural Networks and Animal Behavior written by Magnus Enquist and published by Princeton University Press. This book was released on 2005-09-04 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: How can we make better sense of animal behavior by using what we know about the brain? This is the first book that attempts to answer this important question by applying neural network theory. Scientists create Artificial Neural Networks (ANNs) to make models of the brain. These networks mimic the architecture of a nervous system by connecting elementary neuron-like units into networks in which they stimulate or inhibit each other's activity in much the same way neurons do. This book shows how scientists can employ ANNs to analyze animal behavior, explore the general principles of the nervous systems, and test potential generalizations among species. The authors focus on simple neural networks to show how ANNs can be investigated by math and by computers. They demonstrate intuitive concepts that make the operation of neural networks more accessible to nonspecialists. The first chapter introduces various approaches to animal behavior and provides an informal introduction to neural networks, their history, and their potential advantages. The second chapter reviews artificial neural networks, including biological foundations, techniques, and applications. The following three chapters apply neural networks to such topics as learning and development, classical instrumental condition, and the role of genes in building brain networks. The book concludes by comparing neural networks to other approaches. It will appeal to students of animal behavior in many disciplines. It will also interest neurobiologists, cognitive scientists, and those from other fields who wish to learn more about animal behavior.
Book Synopsis The Handbook of Brain Theory and Neural Networks by : Michael A. Arbib
Download or read book The Handbook of Brain Theory and Neural Networks written by Michael A. Arbib and published by MIT Press. This book was released on 2003 with total page 1328 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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).
Book Synopsis Neuromorphic Olfaction by : Krishna C. Persaud
Download or read book Neuromorphic Olfaction written by Krishna C. Persaud and published by CRC Press. This book was released on 2016-04-19 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many advances have been made in the last decade in the understanding of the computational principles underlying olfactory system functioning. Neuromorphic Olfaction is a collaboration among European researchers who, through NEUROCHEM (Fp7-Grant Agreement Number 216916)-a challenging and innovative European-funded project-introduce novel computing p
Book Synopsis Models of Neural Networks IV by : J. Leo van Hemmen
Download or read book Models of Neural Networks IV written by J. Leo van Hemmen and published by Springer Science & Business Media. This book was released on 2012-11-09 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume, with chapters by leading researchers in the field, is devoted to early vision and attention, that is, to the first stages of visual information processing. This state-of-the-art look at biological neural networks spans the many subfields, such as computational and experimental neuroscience; anatomy and physiology; visual information processing and scene segmentation; perception at illusory contours; control of visual attention; and paradigms for computing with spiking neurons.
Book Synopsis Neural Network Models of Cognition by : J.W. Donahoe
Download or read book Neural Network Models of Cognition written by J.W. Donahoe and published by Elsevier. This book was released on 1997-09-26 with total page 601 pages. Available in PDF, EPUB and Kindle. Book excerpt: This internationally authored volume presents major findings, concepts, and methods of behavioral neuroscience coordinated with their simulation via neural networks. A central theme is that biobehaviorally constrained simulations provide a rigorous means to explore the implications of relatively simple processes for the understanding of cognition (complex behavior). Neural networks are held to serve the same function for behavioral neuroscience as population genetics for evolutionary science. The volume is divided into six sections, each of which includes both experimental and simulation research: (1) neurodevelopment and genetic algorithms, (2) synaptic plasticity (LTP), (3) sensory/hippocampal systems, (4) motor systems, (5) plasticity in large neural systems (reinforcement learning), and (6) neural imaging and language. The volume also includes an integrated reference section and a comprehensive index.
Book Synopsis Neural Network Perspectives on Cognition and Adaptive Robotics by : A Browne
Download or read book Neural Network Perspectives on Cognition and Adaptive Robotics written by A Browne and published by CRC Press. This book was released on 2019-08-20 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: Featuring an international team of authors, Neural Network Perspectives on Cognition and Adaptive Robotics presents several approaches to the modeling of human cognition and language using neural computing techniques. It also describes how adaptive robotic systems can be produced using neural network architectures. Covering a wide range of mainstream area and trends, each chapter provides the latest information from a different perspective.
Book Synopsis Sensory Neural Networks by : Bahram Nabet
Download or read book Sensory Neural Networks written by Bahram Nabet and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "Sensory information is detected and transformed by sensory neural networks before reaching higher levels of processing. These networks need to perform significant processing tasks while being compatible with the following levels. Lateral inhibition is a mechanism of local neuronal interaction that produces significant global properties. This book discusses those sensory neural networks influenced by nonlinear lateral inhibition. It features biological bases of lateral inhibition models, computational properties of these models that stress their short term adaptive behavior, their relation to recent activity in neural networks and connectionist systems, their use for image processing applications, and their application to motion detection. Descriptions from different technologies of analog hardware implementations of these classes of networks are described and results from implementations that corroborate theoretical analysis and show technologically desirable applications are presented. The book also uses nonlinear mathematical techniques to analyze temporal and spatial behavior of models presented within the text. Sensory Neural Networks: Lateral Inhibition is an interdisciplinary work that will prove useful to neural network theorists, biologists, circuit designers, and vision scientists."--Provided by publisher.
Book Synopsis Neural Network Models of Conditioning and Action by : Michael L. Commons
Download or read book Neural Network Models of Conditioning and Action written by Michael L. Commons and published by Routledge. This book was released on 2016-09-19 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: Originally published in 1991, this title was the result of a symposium held at Harvard University. It presents some of the exciting interdisciplinary developments of the time that clarify how animals and people learn to behave adaptively in a rapidly changing environment. The contributors focus on aspects of how recognition learning, reinforcement learning, and motor learning interact to generate adaptive goal-oriented behaviours that can satisfy internal needs – an area of inquiry as important for understanding brain function as it is for designing new types of freely moving autonomous robots. Since the authors agree that a dynamic analysis of system interactions is needed to understand these challenging phenomena – and neural network models provide a natural framework for representing and analysing such interactions – all the articles either develop neural network models or provide biological constraints for guiding and testing their design.
Book Synopsis Modelling Perception with Artificial Neural Networks by : Colin R. Tosh
Download or read book Modelling Perception with Artificial Neural Networks written by Colin R. Tosh and published by Cambridge University Press. This book was released on 2010-06-24 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: Studies of the evolution of animal signals and sensory behaviour have more recently shifted from considering 'extrinsic' (environmental) determinants to 'intrinsic' (physiological) ones. The drive behind this change has been the increasing availability of neural network models. With contributions from experts in the field, this book provides a complete survey of artificial neural networks. The book opens with two broad, introductory level reviews on the themes of the book: neural networks as tools to explore the nature of perceptual mechanisms, and neural networks as models of perception in ecology and evolutionary biology. Later chapters expand on these themes and address important methodological issues when applying artificial neural networks to study perception. The final chapter provides perspective by introducing a neural processing system in a real animal. The book provides the foundations for implementing artificial neural networks, for those new to the field, along with identifying potential research areas for specialists.
