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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

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.

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

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.

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

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.

Advances in Neural Information Processing Systems 12

Advances in Neural Information Processing Systems 12 PDF Author: Sara A. Solla
Publisher: MIT Press
ISBN: 9780262194501
Category : Computers
Languages : en
Pages : 1124

Book Description
The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. It draws preeminent academic researchers from around the world and is widely considered to be a showcase conference for new developments in network algorithms and architectures. The broad range of interdisciplinary research areas represented includes computer science, neuroscience, statistics, physics, cognitive science, and many branches of engineering, including signal processing and control theory. Only about 30 percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. These proceedings contain all of the papers that were presented.

Advances in Neural Information Processing Systems 9

Advances in Neural Information Processing Systems 9 PDF Author: Michael C. Mozer
Publisher: MIT Press
ISBN: 9780262100656
Category : Computers
Languages : en
Pages : 1128

Book Description
The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. It draws preeminent academic researchers from around the world and is widely considered to be a showcase conference for new developments in network algorithms and architectures. The broad range of interdisciplinary research areas represented includes neural networks and genetic algorithms, cognitive science, neuroscience and biology, computer science, AI, applied mathematics, physics, and many branches of engineering. Only about 30% of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. All of the papers presented appear in these proceedings.

Process Neural Networks

Process Neural Networks PDF Author: Xingui He
Publisher: Springer Science & Business Media
ISBN: 3540737626
Category : Computers
Languages : en
Pages : 240

Book Description
For the first time, this book sets forth the concept and model for a process neural network. You’ll discover how a process neural network expands the mapping relationship between the input and output of traditional neural networks and greatly enhances the expression capability of artificial neural networks. Detailed illustrations help you visualize information processing flow and the mapping relationship between inputs and outputs.

Advances in Neural Information Processing Systems 8

Advances in Neural Information Processing Systems 8 PDF Author: David S. Touretzky
Publisher: MIT Press
ISBN: 9780262201070
Category : Computers
Languages : en
Pages : 1128

Book Description
The past decade has seen greatly increased interaction between theoretical work in neuroscience, cognitive science and information processing, and experimental work requiring sophisticated computational modeling. The 152 contributions in NIPS 8 focus on a wide variety of algorithms and architectures for both supervised and unsupervised learning. They are divided into nine parts: Cognitive Science, Neuroscience, Theory, Algorithms and Architectures, Implementations, Speech and Signal Processing, Vision, Applications, and Control. Chapters describe how neuroscientists and cognitive scientists use computational models of neural systems to test hypotheses and generate predictions to guide their work. This work includes models of how networks in the owl brainstem could be trained for complex localization function, how cellular activity may underlie rat navigation, how cholinergic modulation may regulate cortical reorganization, and how damage to parietal cortex may result in neglect. Additional work concerns development of theoretical techniques important for understanding the dynamics of neural systems, including formation of cortical maps, analysis of recurrent networks, and analysis of self- supervised learning. Chapters also describe how engineers and computer scientists have approached problems of pattern recognition or speech recognition using computational architectures inspired by the interaction of populations of neurons within the brain. Examples are new neural network models that have been applied to classical problems, including handwritten character recognition and object recognition, and exciting new work that focuses on building electronic hardware modeled after neural systems. A Bradford Book

Advances in Neural Information Processing Systems 15

Advances in Neural Information Processing Systems 15 PDF Author: Suzanna Becker
Publisher: MIT Press
ISBN: 9780262025508
Category : Computers
Languages : en
Pages : 1738

Book Description
Proceedings of the 2002 Neural Information Processing Systems Conference.

Advances in Neural Information Processing Systems 10

Advances in Neural Information Processing Systems 10 PDF Author: Michael I. Jordan
Publisher: MIT Press
ISBN: 9780262100762
Category : Computers
Languages : en
Pages : 1114

Book Description
The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. These proceedings contain all of the papers that were presented.

Neural Information Processing and VLSI

Neural Information Processing and VLSI PDF Author: Bing J. Sheu
Publisher: Springer Science & Business Media
ISBN: 1461522471
Category : Technology & Engineering
Languages : en
Pages : 569

Book Description
Neural Information Processing and VLSI provides a unified treatment of this important subject for use in classrooms, industry, and research laboratories, in order to develop advanced artificial and biologically-inspired neural networks using compact analog and digital VLSI parallel processing techniques. Neural Information Processing and VLSI systematically presents various neural network paradigms, computing architectures, and the associated electronic/optical implementations using efficient VLSI design methodologies. Conventional digital machines cannot perform computationally-intensive tasks with satisfactory performance in such areas as intelligent perception, including visual and auditory signal processing, recognition, understanding, and logical reasoning (where the human being and even a small living animal can do a superb job). Recent research advances in artificial and biological neural networks have established an important foundation for high-performance information processing with more efficient use of computing resources. The secret lies in the design optimization at various levels of computing and communication of intelligent machines. Each neural network system consists of massively paralleled and distributed signal processors with every processor performing very simple operations, thus consuming little power. Large computational capabilities of these systems in the range of some hundred giga to several tera operations per second are derived from collectively parallel processing and efficient data routing, through well-structured interconnection networks. Deep-submicron very large-scale integration (VLSI) technologies can integrate tens of millions of transistors in a single silicon chip for complex signal processing and information manipulation. The book is suitable for those interested in efficient neurocomputing as well as those curious about neural network system applications. It has been especially prepared for use as a text for advanced undergraduate and first year graduate students, and is an excellent reference book for researchers and scientists working in the fields covered.

Handbook on Neural Information Processing

Handbook on Neural Information Processing PDF Author: Monica Bianchini
Publisher: Springer Science & Business Media
ISBN: 3642366570
Category : Technology & Engineering
Languages : en
Pages : 547

Book Description
This handbook presents some of the most recent topics in neural information processing, covering both theoretical concepts and practical applications. The contributions include: Deep architectures Recurrent, recursive, and graph neural networks Cellular neural networks Bayesian networks Approximation capabilities of neural networks Semi-supervised learning Statistical relational learning Kernel methods for structured data Multiple classifier systems Self organisation and modal learning Applications to content-based image retrieval, text mining in large document collections, and bioinformatics This book is thought particularly for graduate students, researchers and practitioners, willing to deepen their knowledge on more advanced connectionist models and related learning paradigms.