Theory of Neural Information Processing Systems

Theory of Neural Information Processing Systems PDF Author: A.C.C. Coolen
Publisher: OUP Oxford
ISBN: 9780191583001
Category : Neural networks (Computer science)
Languages : en
Pages : 596

Get Book Here

Book Description
Theory of Neural Information Processing Systems provides an explicit, coherent, and up-to-date account of the modern theory of neural information processing systems. It has been carefully developed for graduate students from any quantitative discipline, including mathematics, computer science, physics, engineering or biology, and has been thoroughly class-tested by the authors over a period of some 8 years. Exercises are presented throughout the text and notes on historical background and further reading guide the student into the literature. All mathematical details are included and appendices provide further background material, including probability theory, linear algebra and stochastic processes, making this textbook accessible to a wide audience.

An Introduction to Neural Information Processing

An Introduction to Neural Information Processing PDF Author: Peiji Liang
Publisher: Springer
ISBN: 9401773939
Category : Medical
Languages : en
Pages : 338

Get Book Here

Book Description
This book provides an overview of neural information processing research, which is one of the most important branches of neuroscience today. Neural information processing is an interdisciplinary subject, and the merging interaction between neuroscience and mathematics, physics, as well as information science plays a key role in the development of this field. This book begins with the anatomy of the central nervous system, followed by an introduction to various information processing models at different levels. The authors all have extensive experience in mathematics, physics and biomedical engineering, and have worked in this multidisciplinary area for a number of years. They present classical examples of how the pioneers in this field used theoretical analysis, mathematical modeling and computer simulation to solve neurobiological problems, and share their experiences and lessons learned. The book is intended for researchers and students with a mathematics, physics or informatics background who are interested in brain research and keen to understand the necessary neurobiology and how they can use their specialties to address neurobiological problems. It is also provides inspiration for neuroscience students who are interested in learning how to use mathematics, physics or informatics approaches to solve problems in their field.

Theory of Neural Information Processing Systems

Theory of Neural Information Processing Systems PDF Author: A.C.C. Coolen
Publisher: OUP Oxford
ISBN: 9780191583001
Category : Neural networks (Computer science)
Languages : en
Pages : 596

Get Book Here

Book Description
Theory of Neural Information Processing Systems provides an explicit, coherent, and up-to-date account of the modern theory of neural information processing systems. It has been carefully developed for graduate students from any quantitative discipline, including mathematics, computer science, physics, engineering or biology, and has been thoroughly class-tested by the authors over a period of some 8 years. Exercises are presented throughout the text and notes on historical background and further reading guide the student into the literature. All mathematical details are included and appendices provide further background material, including probability theory, linear algebra and stochastic processes, making this textbook accessible to a wide audience.

Artificial Neural Networks as Models of Neural Information Processing

Artificial Neural Networks as Models of Neural Information Processing PDF Author: Marcel van Gerven
Publisher: Frontiers Media SA
ISBN: 2889454010
Category :
Languages : en
Pages : 220

Get Book Here

Book Description
Modern neural networks gave rise to major breakthroughs in several research areas. In neuroscience, we are witnessing a reappraisal of neural network theory and its relevance for understanding information processing in biological systems. The research presented in this book provides various perspectives on the use of artificial neural networks as models of neural information processing. We consider the biological plausibility of neural networks, performance improvements, spiking neural networks and the use of neural networks for understanding brain function.

An Introduction to Neural and Electronic Networks

An Introduction to Neural and Electronic Networks PDF Author: Steven F. Zornetzer
Publisher:
ISBN:
Category : Computers
Languages : en
Pages : 532

Get Book Here

Book Description
This is a presentation of research and theory from the disciplines that provide the foundations of neural network research: neurobiology, physics, computer science, electrical engineering, mathematics and psychology. It shows how neural networks and neurocomputing represent radical departures from conventional approaches to digital computers, in terms of algorithms as well as architecture. More than 200 line drawings illustrate the many facets of and approaches to neural networks research. This second edition contains new chapters on computational models of hippocampal and cerebellar function, nonlinear information processing, adaptive filtering and pattern recognition, and digital VLSI architecture. Its interdisciplinary emphasis is aimed at a wide array of researchers and students - from neurobiologists to psychologists.

Human Information Processing

Human Information Processing PDF Author: Peter H. Lindsay
Publisher: Academic Press
ISBN: 1483218570
Category : Psychology
Languages : en
Pages : 770

Get Book Here

Book Description
Human Information Processing: An Introduction to Psychology aims to convey the excitement of modern experimental psychology to the beginning student. The book discusses the organization of auditory perceptions; neural information processing; and the theories of pattern recognition. The text also describes the visual system; the dimensions of vision; the auditory system; and the dimensions of sound. The neural basis of memory; transient memories; the structure of memory; and memory processes are also considered. The book further tackles language acquisition; the process of learning and cognitive development; problem solving; and decision making. The text also looks into motivation and the biochemical responses to stress. Psychologists and students taking psychology and related courses will find the book useful."

Neural Information Processing: Research and Development

Neural Information Processing: Research and Development PDF Author: Jagath Chandana Rajapakse
Publisher: Springer
ISBN: 3540399356
Category : Technology & Engineering
Languages : en
Pages : 487

Get Book Here

Book Description
The field of neural information processing has two main objects: investigation into the functioning of biological neural networks and use of artificial neural networks to sol ve real world problems. Even before the reincarnation of the field of artificial neural networks in mid nineteen eighties, researchers have attempted to explore the engineering of human brain function. After the reincarnation, we have seen an emergence of a large number of neural network models and their successful applications to solve real world problems. This volume presents a collection of recent research and developments in the field of neural information processing. The book is organized in three Parts, i.e., (1) architectures, (2) learning algorithms, and (3) applications. Artificial neural networks consist of simple processing elements called neurons, which are connected by weights. The number of neurons and how they are connected to each other defines the architecture of a particular neural network. Part 1 of the book has nine chapters, demonstrating some of recent neural network architectures derived either to mimic aspects of human brain function or applied in some real world problems. Muresan provides a simple neural network model, based on spiking neurons that make use of shunting inhibition, which is capable of resisting small scale changes of stimulus. Hoshino and Zheng simulate a neural network of the auditory cortex to investigate neural basis for encoding and perception of vowel sounds.

Advances in Neural Information Processing Systems 7

Advances in Neural Information Processing Systems 7 PDF Author: Gerald Tesauro
Publisher: MIT Press
ISBN: 9780262201049
Category : Computers
Languages : en
Pages : 1180

Get Book Here

Book Description
November 28-December 1, 1994, Denver, Colorado NIPS is the longest running annual meeting devoted to Neural Information Processing Systems. Drawing on such disparate domains as neuroscience, cognitive science, computer science, statistics, mathematics, engineering, and theoretical physics, the papers collected in the proceedings of NIPS7 reflect the enduring scientific and practical merit of a broad-based, inclusive approach to neural information processing. The primary focus remains the study of a wide variety of learning algorithms and architectures, for both supervised and unsupervised learning. The 139 contributions are divided into eight parts: Cognitive Science, Neuroscience, Learning Theory, Algorithms and Architectures, Implementations, Speech and Signal Processing, Visual Processing, and Applications. Topics of special interest include the analysis of recurrent nets, connections to HMMs and the EM procedure, and reinforcement- learning algorithms and the relation to dynamic programming. On the theoretical front, progress is reported in the theory of generalization, regularization, combining multiple models, and active learning. Neuroscientific studies range from the large-scale systems such as visual cortex to single-cell electrotonic structure, and work in cognitive scientific is closely tied to underlying neural constraints. There are also many novel applications such as tokamak plasma control, Glove-Talk, and hand tracking, and a variety of hardware implementations, with particular focus on analog VLSI.

Advances in Neural Information Processing Systems

Advances in Neural Information Processing Systems PDF Author: David S. Touretzky
Publisher:
ISBN: 9781558600157
Category :
Languages : en
Pages :

Get Book Here

Book Description


Introduction to Neural Networks

Introduction to Neural Networks PDF Author: Architecture Technology Architecture Technology Corpor
Publisher: Elsevier
ISBN: 1483295303
Category : Computers
Languages : en
Pages : 73

Get Book Here

Book Description
Please note this is a Short Discount publication. Neural network technology has been a curiosity since the early days of computing. Research in the area went into a near dormant state for a number of years, but recently there has been a new increased interest in the subject. This has been due to a number of factors: interest in the military, apparent ease of implementation, and the ability of the technology to develop computers which are able to learn from experience. This report summarizes the topic, providing the reader with an overview of the field and its potential direction. Included is an introduction to the technology and its future directions, as well as a set of examples of possible applications and potential implementation technologies.

Principles of Neural Information Processing

Principles of Neural Information Processing PDF Author: Werner v. Seelen
Publisher: Springer
ISBN: 3319201131
Category : Technology & Engineering
Languages : en
Pages : 110

Get Book Here

Book Description
In this fundamental book the authors devise a framework that describes the working of the brain as a whole. It presents a comprehensive introduction to the principles of Neural Information Processing as well as recent and authoritative research. The books ́ guiding principles are the main purpose of neural activity, namely, to organize behavior to ensure survival, as well as the understanding of the evolutionary genesis of the brain. Among the developed principles and strategies belong self-organization of neural systems, flexibility, the active interpretation of the world by means of construction and prediction as well as their embedding into the world, all of which form the framework of the presented description. Since, in brains, their partial self-organization, the lifelong adaptation and their use of various methods of processing incoming information are all interconnected, the authors have chosen not only neurobiology and evolution theory as a basis for the elaboration of such a framework but also systems and signal theory. The most important message of the book and authors is: brains are evolved as a whole and a description of parts although necessary lets one miss the wood for the trees.